# Monitoring metrics in an Amazon RDS instance
In the following sections, you can find an overview of Amazon RDS monitoring and an explanation about how to access metrics. To learn how to monitor events, logs, and database activity streams, see [Monitoring events, logs, and streams in an Amazon RDS DB instance](CHAP_Monitor_Logs_Events.md).
**Topics**
+ [
## Monitoring plan
](#MonitoringOverview.plan)
+ [
## Performance baseline
](#MonitoringOverview.baseline)
+ [
## Performance guidelines
](#MonitoringOverview.guidelines)
+ [
# Monitoring tools for Amazon RDS
](MonitoringOverview.md)
+ [
# Viewing instance status
](accessing-monitoring.md)
+ [
# Recommendations from Amazon RDS
](monitoring-recommendations.md)
+ [
# Viewing metrics in the Amazon RDS console
](USER_Monitoring.md)
+ [
# Viewing combined metrics with the Performance Insights dashboard
](Viewing_Unifiedmetrics.md)
+ [
# Monitoring Amazon RDS metrics with Amazon CloudWatch
](monitoring-cloudwatch.md)
+ [
# Monitoring Amazon RDS databases with CloudWatch Database Insights
](USER_DatabaseInsights.md)
+ [
# Monitoring DB load with Performance Insights on Amazon RDS
](USER_PerfInsights.md)
+ [
# Analyzing performance anomalies with Amazon DevOps Guru for Amazon RDS
](devops-guru-for-rds.md)
+ [
# Monitoring OS metrics with Enhanced Monitoring
](USER_Monitoring.OS.md)
+ [
# Metrics reference for Amazon RDS
](metrics-reference.md)
## Monitoring plan
Before you start monitoring Amazon RDS, create a monitoring plan. This plan should answer the following questions:
+ What are your monitoring goals?
+ Which resources will you monitor?
+ How often will you monitor these resources?
+ Which monitoring tools will you use?
+ Who will perform the monitoring tasks?
+ Whom should be notified when something goes wrong?
## Performance baseline
To achieve your monitoring goals, you need to establish a baseline. To do this, measure performance under different load conditions at various times in your Amazon RDS environment. You can monitor metrics such as the following:
+ Network throughput
+ Client connections
+ I/O for read, write, or metadata operations
+ Burst credit balances for your DB instances
We recommend that you store historical performance data for Amazon RDS. Using the stored data, you can compare current performance against past trends. You can also distinguish normal performance patterns from anomalies, and devise techniques to address issues.
## Performance guidelines
In general, acceptable values for performance metrics depend on what your application is doing relative to your baseline. Investigate consistent or trending variances from your baseline. The following metrics are often the source of performance issues:
+ **High CPU or RAM consumption** – High values for CPU or RAM consumption might be appropriate, if they're in keeping with your goals for your application (like throughput or concurrency) and are expected.
+ **Disk space consumption** – Investigate disk space consumption if space used is consistently at or above 85 percent of the total disk space. See if it is possible to delete data from the instance or archive data to a different system to free up space.
+ **Network traffic** – For network traffic, talk with your system administrator to understand what expected throughput is for your domain network and internet connection. Investigate network traffic if throughput is consistently lower than expected.
+ **Database connections** – If you see high numbers of user connections and also decreases in instance performance and response time, consider constraining database connections. The best number of user connections for your DB instance varies based on your instance class and the complexity of the operations being performed. To determine the number of database connections, associate your DB instance with a parameter group where the `User Connections` parameter is set to a value other than 0 (unlimited). You can either use an existing parameter group or create a new one. For more information, see [Parameter groups for Amazon RDS](USER_WorkingWithParamGroups.md).
+ **IOPS metrics** – The expected values for IOPS metrics depend on disk specification and server configuration, so use your baseline to know what is typical. Investigate if values are consistently different than your baseline. For best IOPS performance, make sure that your typical working set fits into memory to minimize read and write operations.
When performance falls outside your established baseline, you might need to make changes to optimize your database availability for your workload. For example, you might need to change the instance class of your DB instance. Or you might need to change the number of DB instances and read replicas that are available for clients.
# Monitoring tools for Amazon RDS
Monitoring is an important part of maintaining the reliability, availability, and performance of Amazon RDS and your other AWS solutions. AWS provides various monitoring tools to watch Amazon RDS, report when something is wrong, and take automatic actions when appropriate.
**Topics**
+ [
## Automated monitoring tools
](#MonitoringOverview.tools.automated)
+ [
## Manual monitoring tools
](#monitoring_manual_tools)
## Automated monitoring tools
We recommend that you automate monitoring tasks as much as possible.
**Topics**
+ [
### Amazon RDS instance status and recommendations
](#MonitoringOverview.tools.automated.rds)
+ [
### Amazon CloudWatch metrics for Amazon RDS
](#MonitoringOverview.tools.automated.integrated)
+ [
### Amazon RDS Performance Insights and operating-system monitoring
](#MonitoringOverview.tools.automated.metrics.rds)
+ [
### Integrated services
](#MonitoringOverview.tools.automated.integrated.events-logs-streams)
### Amazon RDS instance status and recommendations
You can use the following automated tools to watch Amazon RDS and report when something is wrong:
+ **Amazon RDS instance status** — View details about the current status of your instance by using the Amazon RDS console, the AWS CLI, or the RDS API.
+ **Amazon RDS recommendations** — Respond to automated recommendations for database resources, such as DB instances, read replicas, and DB parameter groups. For more information, see [Recommendations from Amazon RDS](monitoring-recommendations.md).
### Amazon CloudWatch metrics for Amazon RDS
Amazon RDS integrates with Amazon CloudWatch for additional monitoring capabilities.
+ **Amazon CloudWatch** – This service monitors your AWS resources and the applications you run on AWS in real time. You can use the following Amazon CloudWatch features with Amazon RDS:
+ **Amazon CloudWatch metrics** – Amazon RDS automatically sends metrics to CloudWatch every minute for each active database. You don't get additional charges for Amazon RDS metrics in CloudWatch. For more information, see [Monitoring Amazon RDS metrics with Amazon CloudWatch](monitoring-cloudwatch.md).
+ **Amazon CloudWatch alarms** – You can watch a single Amazon RDS metric over a specific time period. You can then perform one or more actions based on the value of the metric relative to a threshold that you set. For more information, see [Monitoring Amazon RDS metrics with Amazon CloudWatch](monitoring-cloudwatch.md).
### Amazon RDS Performance Insights and operating-system monitoring
You can use the following automated tools to monitor Amazon RDS performance:
+ **Amazon RDS Performance Insights** – Assess the load on your database, and determine when and where to take action. For more information, see [Monitoring DB load with Performance Insights on Amazon RDS](USER_PerfInsights.md).
+ **Amazon RDS Enhanced Monitoring** – Look at metrics in real time for the operating system. For more information, see [Monitoring OS metrics with Enhanced Monitoring](USER_Monitoring.OS.md).
### Integrated services
The following AWS services are integrated with Amazon RDS:
+ *Amazon EventBridge* is a serverless event bus service that makes it easy to connect your applications with data from a variety of sources. For more information, see [Monitoring Amazon RDS events](working-with-events.md).
+ *Amazon CloudWatch Logs* lets you monitor, store, and access your log files from Amazon RDS instances, CloudTrail, and other sources. For more information, see [Monitoring Amazon RDS log files](USER_LogAccess.md).
+ *AWS CloudTrail* captures API calls and related events made by or on behalf of your AWS account and delivers the log files to an Amazon S3 bucket that you specify. For more information, see [Monitoring Amazon RDS API calls in AWS CloudTrail](logging-using-cloudtrail.md).
+ *Database Activity Streams* is an Amazon RDS feature that provides a near-real-time stream of the activity in your Oracle DB instance. For more information, see [Monitoring Amazon RDS with Database Activity Streams](DBActivityStreams.md).
## Manual monitoring tools
You need to manually monitor those items that the CloudWatch alarms don't cover. The Amazon RDS, CloudWatch, AWS Trusted Advisor and other AWS console dashboards provide an at-a-glance view of the state of your AWS environment. We recommend that you also check the log files on your DB instance.
+ From the Amazon RDS console, you can monitor the following items for your resources:
+ The number of connections to a DB instance
+ The amount of read and write operations to a DB instance
+ The amount of storage that a DB instance is currently using
+ The amount of memory and CPU being used for a DB instance
+ The amount of network traffic to and from a DB instance
+ From the Trusted Advisor dashboard, you can review the following cost optimization, security, fault tolerance, and performance improvement checks:
+ Amazon RDS Idle DB Instances
+ Amazon RDS Security Group Access Risk
+ Amazon RDS Backups
+ Amazon RDS Multi-AZ
For more information on these checks, see [Trusted Advisor best practices (checks)](https://aws.amazon.com/premiumsupport/trustedadvisor/best-practices/).
+ CloudWatch home page shows:
+ Current alarms and status
+ Graphs of alarms and resources
+ Service health status
In addition, you can use CloudWatch to do the following:
+ Create [customized dashboards](https://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/CloudWatch_Dashboards.html) to monitor the services that you care about.
+ Graph metric data to troubleshoot issues and discover trends.
+ Search and browse all your AWS resource metrics.
+ Create and edit alarms to be notified of problems.
# Viewing instance status
Using the Amazon RDS console, you can quickly access the status of your DB instance.
**Topics**
+ [
## Viewing Amazon RDSDB instance status
](#Overview.DBInstance.Status)
## Viewing Amazon RDSDB instance status
The status of a DB instance indicates its current operational state. You can use the following procedures to view the DB instance status in the Amazon RDS console, the AWS CLI command, or the API operation.
**Note**
Amazon RDS also uses another status called *maintenance status*, which is shown in the **Maintenance** column of the Amazon RDS console. This value indicates the status of any maintenance patches that need to be applied to a DB instance. Maintenance status is independent of DB instance status. For more information about maintenance status, see [Applying updates to a DB instance ](USER_UpgradeDBInstance.Maintenance.md#USER_UpgradeDBInstance.OSUpgrades).
Find the possible status values for DB instances in the following table. This table also shows whether you will be billed for the DB instance and storage, billed only for storage, or not billed. For all DB instance statuses, you are always billed for backup usage.
| DB instance status | Billed | Description |
| --- | --- | --- |
| **available** | Billed | The DB instance is available for modifications. |
| **backing-up** | Billed | The DB instance is currently being backed up. |
| **configuring-enhanced-monitoring** | Billed | Enhanced Monitoring is being enabled or disabled for this DB instance. |
| **configuring-iam-database-auth** | Billed | AWS Identity and Access Management (IAM) database authentication is being enabled or disabled for this DB instance. |
| **configuring-log-exports** | Billed | Publishing log files to Amazon CloudWatch Logs is being enabled or disabled for this DB instance. |
| **converting-to-vpc** | Billed | The DB instance is being converted from a DB instance that is not in an Amazon Virtual Private Cloud (Amazon VPC) to a DB instance that is in an Amazon VPC. |
| **creating** | Not billed (non-PITR) Billed (PITR only) | The DB instance is being created. The DB instance is inaccessible while it is being created. If you restore a database during point-in-time recovery (PITR), you're billed while the database is in the **creating** state. This is the only scenario in which the **creating** state incurs charges. |
| **delete-precheck** | Not billed | Amazon RDS is validating that read replicas are safe to delete. |
| **deleting** | Not billed | The DB instance is being deleted. |
| **failed** | Not billed | The DB instance has failed and Amazon RDS can't recover it. Perform a point-in-time restore to the latest restorable time of the DB instance to recover the data. |
| **inaccessible-encryption-credentials** | Not billed | The AWS KMS key used to encrypt or decrypt the DB instance can't be accessed or recovered. |
| **inaccessible-encryption-credentials-recoverable** | Billed for storage | The KMS key used to encrypt or decrypt the DB instance can't be accessed. However, if the KMS key is active, restarting the DB instance can recover it. For more information, see [Encrypting a DB instance](Overview.Encryption.md#Overview.Encryption.Enabling). |
| **incompatible-create** | Not billed | Amazon RDS is attempting to create a DB instance but can't do so because resources are incompatible with your DB instance. This status can occur if, for example, the instance profile for your DB instance doesn't have the correct permissions. |
| **incompatible-network** | Not billed | Amazon RDS is attempting to perform a recovery action on a DB instance but can't do so because the VPC is in a state that prevents the action from being completed. This status can occur if, for example, all available IP addresses in a subnet are in use and Amazon RDS can't get an IP address for the DB instance. |
| **incompatible-option-group** | Billed | Amazon RDS attempted to apply an option group change but can't do so, and Amazon RDS can't roll back to the previous option group state. For more information, check the **Recent Events** list for the DB instance. This status can occur if, for example, the option group contains an option such as TDE and the DB instance doesn't contain encrypted information. |
| **incompatible-parameters** | Billed | Amazon RDS can't start the DB instance because the parameters specified in the DB instance's DB parameter group aren't compatible with the DB instance. Revert the parameter changes or make them compatible with the DB instance to regain access to your DB instance. For more information about the incompatible parameters, check the **Recent Events** list for the DB instance. |
| **incompatible-restore** | Not billed | Amazon RDS can't do a point-in-time restore. Common causes for this status include using temp tables, using MyISAM tables with MySQL, or using Aria tables with MariaDB. |
| insufficient-capacity | Not billed | Amazon RDS can't create your instance because sufficient capacity isn't currently available. To create your DB instance in the same AZ with the same instance type, delete your DB instance, wait a few hours, and try to create again. Alternatively, create a new instance using a different instance class or AZ. |
| **maintenance** | Billed | Amazon RDS is applying a maintenance update to the DB instance. This status is used for instance-level maintenance that RDS schedules well in advance. |
| **modifying** | Billed | The DB instance is being modified because of a customer request to modify the DB instance. |
| **moving-to-vpc** | Billed | The DB instance is being moved to a new Amazon Virtual Private Cloud (Amazon VPC). |
| **rebooting** | Billed | The DB instance is being rebooted because of a customer request or an Amazon RDS process that requires the rebooting of the DB instance. |
| **resetting-master-credentials** | Billed | The master credentials for the DB instance are being reset because of a customer request to reset them. |
| **renaming** | Billed | The DB instance is being renamed because of a customer request to rename it. |
| **restore-error** | Billed | The DB instance encountered an error attempting to restore to a point-in-time or from a snapshot. |
| **starting** | Billed for storage | The DB instance is starting. |
| **stopped** | Billed for storage | The DB instance is stopped. |
| **stopping** | Billed for storage | The DB instance is being stopped. |
| **storage-config-upgrade** | Billed | The storage file system configuration of the DB instance is being upgraded. This status only applies to green databases within a blue/green deployment, or to DB instance read replicas. |
| **storage-full** | Billed | The DB instance has reached its storage capacity allocation. This is a critical status, and we recommend that you fix this issue immediately. To do so, scale up your storage by modifying the DB instance. To avoid this situation, set Amazon CloudWatch alarms to warn you when storage space is getting low. |
| storage-initialization | Billed | The DB instance is loading data blocks from Amazon S3 to optimize volume performance after being restored from a snapshot. It remains available for operations, but performance mights not be at its fullest until initialization completes. |
| **storage-optimization** | Billed | Amazon RDS is optimizing the storage of your DB instance. The storage optimization process is usually short, but can sometimes take up to and even beyond 24 hours. During storage optimization, the DB instance remains available. Storage optimization is a background process that doesn't affect the instance's availability. |
| **upgrading** | Billed | The database engine or operating system version is being upgraded. |
| **upgrade-failed** | Not billed | The DB instance has failed to upgrade to a supported version. Aurora creates a final snapshot with the prefix `rds-final`. |
### Console
**To view the status of a DB instance**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, choose **Databases**.
The **Databases page** appears with the list of DB instances. For each DB instance , the status value is displayed.
![\[View the status of a DB instance\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/RDS_instance_status.png)
### CLI
To view DB instance and its status information by using the AWS CLI, use the [describe-db-instances](https://docs.aws.amazon.com/cli/latest/reference/rds/describe-db-instances.html) command. For example, the following AWS CLI command lists all the DB instances information .
```
aws rds describe-db-instances
```
To view a specific DB instance and its status, call the [describe-db-instances](https://docs.aws.amazon.com/cli/latest/reference/rds/describe-db-instances.html) command with the following option:
+ `DBInstanceIdentifier` – The name of the DB instance.
```
aws rds describe-db-instances --db-instance-identifier mydbinstance
```
To view just the status of all the DB instances, use the following query in AWS CLI.
```
aws rds describe-db-instances --query 'DBInstances[*].[DBInstanceIdentifier,DBInstanceStatus]' --output table
```
### API
To view the status of the DB instance using the Amazon RDS API, call the [DescribeDBInstances](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_DescribeDBInstances.html) operation.
# Recommendations from Amazon RDS
Amazon RDS provides automated recommendations for database resources, such as DB instances, read replicas, and DB parameter groups. These recommendations provide best practice guidance by analyzing DB instance configuration, usage, and performance data.
Amazon RDS Performance Insights monitors specific metrics and automatically creates thresholds by analyzing what levels are considered potentially problematic for a specified resource. When new metric values cross a predefined threshold over a given period of time, Performance Insights generates a proactive recommendation. This recommendation helps to prevent future database performance impact. For example, the "Idle In Transaction" recommendation is generated for RDS for PostgreSQL instances when the sessions connected to the database are not performing active work, but can keep database resources blocked. To receive proactive recommendations, you must turn on Performance Insights with a paid tier retention period. For information about turning on Performance Insights, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md). For information about pricing and data retention for Performance Insights see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
DevOps Guru for RDS monitors certain metrics to detect when the metric's behavior becomes highly unusual or anomalous. These anomalies are reported as reactive insights with recommendations. For example, DevOps Guru for RDS might recommend you to consider increasing CPU capacity or investigate wait events that are contributing to DB load. DevOps Guru for RDS also provides threshold based proactive recommendations. For these recommendations, you must turn on DevOps Guru for RDS. For information about turning on DevOps Guru for RDS, see [Turning on DevOps Guru and specifying resource coverage](devops-guru-for-rds.md#devops-guru-for-rds.configuring.coverage).
Recommendations will be in any of the following status: active, dismissed, pending, or resolved. Resolved recommendations are available for 365 days.
You can view or dismiss the recommendations. You can apply a configuration based active recommendation immediately, schedule it in the next maintenance window, or dismiss it. For threshold based proactive and machine learning based reactive recommendations, you need to review the suggested cause of the issue and then perform the recommended actions to fix the issue.
Recommendations are supported in the following AWS Regions:
+ US East (Ohio)
+ US East (N. Virginia)
+ US West (N. California)
+ US West (Oregon)
+ Asia Pacific (Mumbai)
+ Asia Pacific (Seoul)
+ Asia Pacific (Singapore)
+ Asia Pacific (Sydney)
+ Asia Pacific (Tokyo)
+ Canada (Central)
+ Europe (Frankfurt)
+ Europe (Ireland)
+ Europe (London)
+ Europe (Paris)
+ Europe (Stockholm)
+ South America (São Paulo)
Learn to view, apply, dismiss, and modify recommendations from Amazon RDS in the following sections.
**Topics**
+ [
# Viewing Amazon RDS recommendations
](UserRecommendationsView.md)
+ [
# Applying Amazon RDS recommendations
](USERRecommendationsManage.ApplyRecommendation.md)
+ [
# Dismissing Amazon RDS recommendations
](USERRecommendationsManage.DismissRecommendation.md)
+ [
# Modifying dismissed Amazon RDS recommendations to active recommendations
](USERRecommendationsManage.DismissToActiveRecommendation.md)
+ [
# Recommendations from Amazon RDS reference
](USERRecommendationsManage.RecommendationReference.md)
# Viewing Amazon RDS recommendations
Using the Amazon RDS console, you can view Amazon RDS recommendations for your database resources.
## Console
**To view the Amazon RDS recommendations**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, do any of the following:
+ Choose **Recommendations**. The number of active recommendations for your resources and the number of recommendations with the highest severity generated in the last month are available next to **Recommendations**. To find the number of active recommendations for each severity, choose the number that shows the highest severity.
![\[Select Recommendations in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/recommendations-select.png)
By default, the **Recommendations** page displays a list of new recommendations in the last month. Amazon RDS gives recommendations for all the resources in your account and sorts the recommendations by their severity.
![\[Main Recommendations page in the console which contains all the recommendations\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_List.png)
You can choose a recommendation to view a section at the bottom of the page which contains the affected resources and details of how the recommendation will be applied.
+ In the **Databases** page, choose **Recommendations** for a resource.
![\[Recommendation option selected on Databases page in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_DBpage.png)
The **Recommendations** tab displays the recommendations and its details for the selected resource.
![\[Recommendations tab on Databases page in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/RecommendationsTab_DBpage.png)
The following details are available for the recommendations:
+ **Severity** – The implication level of the issue. The severity levels are **High**, **Medium**, **Low**, and **Informational**.
+ **Detection** – The number of affected resources and a short description of the issue. Choose this link to view the recommendation and the analysis details.
+ **Recommendation** – A short description of the recommended action to apply.
+ **Impact** – A short description of the possible impact when the recommendation isn't applied.
+ **Category** – The type of recommendation. The categories are **Performance efficiency**, **Security**, **Reliability**, **Cost optimization**, **Operational excellence**, and **Sustainability**.
+ **Status** – The current status of the recommendation. The possible statuses are **All**, **Active**, **Dismissed**, **Resolved**, and **Pending**.
+ **Start time** – The time when the issue began. For example, **18 hours ago**.
+ **Last modified** – The time when the recommendation was last updated by the system because of a change in the **Severity**, or the time you responded to the recommendation. For example, **10 hours ago**.
+ **End time** – The time when the issue ended. The time won't display for any continuing issues.
+ **Resource identifier** – The name of one or more resources.
1. (Optional) Choose **Severity** or **Category** operators in the field to filter the list of recommendations.
![\[Recommendations page with severity operation in the console.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_Severity.png)
The recommendations for the selected operation appear.
1. (Optional) Choose any of the following recommendation status:
+ **Active** (default) – Shows the current recommendations that you can apply, schedule it for the next maintenance window, or dismiss.
+ **All** – Shows all the recommendations with the current status.
+ **Dismissed** – Shows the dismissed recommendations.
+ **Resolved** – Shows the recommendations that are resolved.
+ **Pending** – Shows the recommendations whose recommended actions are in progress or scheduled for the next maintenance window.
![\[Recommendations filtered by status in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_Status.png)
1. (Optional) Choose **Relative mode** or **Absolute mode** in **Last modified** to modify the time period. The **Recommendations** page displays the recommendations generated in the time period. The default time period is the last month. In the **Absolute mode**, you can choose the time period, or enter the time in **Start date** and **End date** fields.
![\[Recommendations filtered by time period in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_TimeMode.png)
The recommendations for the set time period display.
Note that you can see all recommendations for resources in your account by setting the range to **All**.
1. (Optional) Choose **Preferences** in the right to customize the details to display. You can choose a page size, wrap the lines of the text, and allow or hide the columns.
1. (Optional) Choose a recommendation and then choose **View details**.
![\[Recommendations page in the console with a selected recommendation and view details button chosen.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_viewDetailsSelect.png)
The recommendation details page appears. The title provides the total count of the resources with the issue detected and the severity.
For information about the components on the details page for an anomaly based reactive recommendation, see [Viewing reactive anomalies](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-rds.analyzing.metrics.html) in the *Amazon DevOps Guru User Guide*.
For information about the components on the details page for a threshold based proactive recommendation, see [Viewing Performance Insights proactive recommendations](USER_PerfInsights.InsightsRecommendationViewDetails.md).
The other automated recommendations display the following components on the recommendation details page:
+ **Recommendation** – A summary of the recommendation and whether downtime is required to apply the recommendation.
![\[Recommendations details page showing Recommendation section in the console.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/RecommendationSummary.png)
+ **Resources affected** – Details of the affected resources.
![\[Recommendations details page showing Resources Affected section in the console.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_AffectedResources.png)
+ **Recommendation details** – Supported engine information, any required associated cost to apply the recommendation, and documentation link to learn more.
![\[Recommendations details page showing Recommendation details section in the console.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/RecommendationDetails.png)
## CLI
To view Amazon RDS recommendations of the DB instances, use the following command in AWS CLI.
```
aws rds describe-db-recommendations
```
## RDS API
To view Amazon RDS recommendations using the Amazon RDS API, use the [DescribeDBRecommendations](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_DescribeDBRecommendations.html) operation.
# Applying Amazon RDS recommendations
To apply Amazon RDS recommendations using the Amazon RDS console, select a configuration based recommendation or an affected resource in the details page. Then, choose to apply the recommendation immediately or schedule it for the next maintenance window. The resource might need to restart for the change to take effect. For a few DB parameter group recommendations, you might need to restart the resources.
The threshold based proactive or anomaly based reactive recommendations won't have the apply option and might need additional review.
## Console
**To apply a configuration based recommendation**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, perform any of the following:
+ Choose **Recommendations**.
The **Recommendations** page appears with the list of all recommendations.
+ Choose **Databases** and then choose **Recommendations** for a resource in the databases page.
The details appear in the **Recommendations** tab for the selected recommendation.
+ Choose **Detection** for an active recommendation in the **Recommendations** page or the **Recommendations** tab in the **Databases** page.
The recommendation details page appears.
1. Choose a recommendation, or one or more affected resources in the recommendation details page, and do any of the following:
+ Choose **Apply** and then choose **Apply immediately** to apply the recommendation immediately.
+ Choose **Apply** and then choose **Apply in next maintenance window** to schedule in the next maintenance window.
The selected recommendation status is updated to pending until the next maintenance window.
![\[An active recommendation selected and Apply button with its options highlighted in the console.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_Apply_Defer.png)
A confirmation window appears.
1. Choose **Confirm application** to apply the recommendation. This window confirms whether the resources need an automatic or manual restart for the changes to take effect.
The following example shows the confirmation window to apply the recommendation immediately.
![\[The confirmation window in the console to apply the recommendation immediately\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_ApplyImmediately.png)
The following example shows the confirmation window to schedule applying the recommendation in the next maintenance window.
![\[The confirmation window in the console to schedule applying the recommendation in the next maintenance window\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_Defer.png)
A banner displays a message when the recommendation applied is successful or has failed.
The following example shows the banner with the successful message.
![\[A banner in the console showing the message with the number of resources that will apply the recommendation\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendation-Apply-Banner.png)
The following example shows the banner with the failure message.
![\[A banner in the console showing the message with the resource that failed to apply the recommendation and the reason for the failure\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendation-Apply-Banner-failure.png)
## RDS API
**To apply a configuration based RDS recommendation using the Amazon RDS API**
1. Use the [DescribeDBRecommendations](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_DescribeDBRecommendations.html) operation. The `RecommendedActions` in the output can have one or more recommended actions.
1. Use the [RecommendedAction](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_RecommendedAction.html) object for each recommended action from step 1. The output contains `Operation` and `Parameters`.
The following example shows the output with one recommended action.
```
"RecommendedActions": [
{
"ActionId": "0b19ed15-840f-463c-a200-b10af1b552e3",
"Title": "Turn on auto backup", // localized
"Description": "Turn on auto backup for my-mysql-instance-1", // localized
"Operation": "ModifyDbInstance",
"Parameters": [
{
"Key": "DbInstanceIdentifier",
"Value": "my-mysql-instance-1"
},
{
"Key": "BackupRetentionPeriod",
"Value": "7"
}
],
"ApplyModes": ["immediately", "next-maintenance-window"],
"Status": "applied"
},
... // several others
],
```
1. Use the `operation` for each recommended action from the output in step 2 and input the `Parameters` values.
1. After the operation in step 2 is successful, use the [ModifyDBRecommendation](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBRecommendation.html) operation to modify the recommendation status.
# Dismissing Amazon RDS recommendations
You can dismiss one or more Amazon RDS recommendations using the Amazon RDS console, AWS CLI, or Amazon RDS API.
## Console
**To dismiss one or more recommendations**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, perform any of the following:
+ Choose **Recommendations**.
The **Recommendations** page appears with the list of all recommendations.
+ Choose **Databases** and then choose **Recommendations** for a resource in the databases page.
The details appear in the **Recommendations** tab for the selected recommendation.
+ Choose **Detection** for an active recommendation in the **Recommendations** page or the **Recommendations** tab in the **Databases** page.
The recommendation details page displays the list of affected resources.
1. Choose one or more recommendation, or one or more affected resources in the recommendation details page, and then choose **Dismiss**.
The following example shows the **Recommendations** page with multiple active recommendations selected to dismiss.
![\[A few active recommendations selected and dismiss button highlighted in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_Dismiss.png)
A banner displays a message when the selected one or more recommendations are dismissed.
The following example shows the banner with the successful message.
![\[A banner in the console showing the message with the number of resources that were successful to dismiss the recommendation\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendation-Dismiss-Banner.png)
The following example shows the banner with the failure message.
![\[A banner in the console showing the message with the resource that failed to dismiss the recommendation\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendation-Dismiss-Banner-failure.png)
## CLI
**To dismiss a RDS recommendation using the AWS CLI**
1. Run the command `aws rds describe-db-recommendations --filters "Name=status,Values=active"`.
The output provides a list of recommendations in `active` status.
1. Find the `recommendationId` for the recommendation that you want to dismiss from step 1.
1. Run the command `>aws rds modify-db-recommendation --status dismissed --recommendationId ` with the `recommendationId` from step 2 to dismiss the recommendation.
## RDS API
To dismiss a RDS recommendation using the Amazon RDS API, use the [ModifyDBRecommendation](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBRecommendation.html) operation.
# Modifying dismissed Amazon RDS recommendations to active recommendations
You can move one or more dismissed Amazon RDS recommendations to active recommendations using the Amazon RDS console, AWS CLI, or Amazon RDS API.
## Console
**To move one or more dismissed recommendations to active recommendations**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, perform any of the following:
+ Choose **Recommendations**.
The **Recommendations** page displays a list of recommendations sorted by the severity for all the resources in your account.
+ Choose **Databases** and then choose **Recommendations** for a resource in the databases page.
The **Recommendations** tab displays the recommendations and its details for the selected resource.
1. Choose one or more dismissed recommendations from the list and then choose **Move to active**.
![\[A few dismissed recommendations selected and Move to active button highlighted in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendations_DismissToActive.png)
A banner displays a successful or failure message when the moving the selected recommendations from dismissed to active status.
The following example shows the banner with the successful message.
![\[a banner in the console showing the message with the number of resources moved successfully from dismissed to active recommendations\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendation-DismissToActive-Banner.png)
The following example shows the banner with the failure message.
![\[a banner in the console showing the message with the resource that failed to move from dismissed to active recommendations\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Recommendation-DismissToActive-Banner-Failure.png)
## CLI
**To change a dismissed RDS recommendation to active recommendation using the AWS CLI**
1. Run the command `aws rds describe-db-recommendations --filters "Name=status,Values=dismissed"`.
The output provides a list of recommendations in `dismissed` status.
1. Find the `recommendationId` for the recommendation that you want to change the status from step 1.
1. Run the command `>aws rds modify-db-recommendation --status active --recommendationId ` with the `recommendationId` from step 2 to change to active recommendation.
## RDS API
To change a dismissed RDS recommendation to active recommendation using the Amazon RDS API, use the [ModifyDBRecommendation](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBRecommendation.html) operation.
# Recommendations from Amazon RDS reference
Amazon RDS generates recommendations for a resource when the resource is created or modified. You can find examples of recommendations from Amazon RDS in the following table.
| Type | Description | Recommendation | Downtime required | Additional information |
| --- | --- | --- | --- | --- |
| Magnetic volume is in use | Your DB instances are using magnetic storage. Magnetic storage isn't recommended for most of the DB instances. Choose a different storage type: General Purpose (SSD) or Provisioned IOPS. | Choose a different storage type: General Purpose (SSD) or Provisioned IOPS. | Yes | [Previous generation volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-volume-types.html#vol-type-prev) in the Amazon EC2 documentation. |
| Resource Automated backups is turned off | Automated backups aren't turned on for your DB instances. Automated backups are recommended because they enable point-in-time recovery of your DB instances. | Turn on automated backups with a retention period of up to 14 days. | Yes | [Enabling automated backups](USER_WorkingWithAutomatedBackups.Enabling.md) [ Demystifying Amazon RDS backup storage costs](https://aws.amazon.com/blogs/database/demystifying-amazon-rds-backup-storage-costs/) on the AWS Database Blog |
| Engine minor version upgrade is required | Your database resources aren't running the latest minor DB engine version. The latest minor version contains the latest security fixes and other improvements. | Upgrade to latest engine version. | Yes | [Upgrading a DB instance engine version](USER_UpgradeDBInstance.Upgrading.md) |
| Enhanced Monitoring is turned off | Your database resources don't have Enhanced Monitoring turned on. Enhanced Monitoring provides real-time operating system metrics for monitoring and troubleshooting. | Turn on Enhanced Monitoring. | No | [Monitoring OS metrics with Enhanced Monitoring](USER_Monitoring.OS.md) |
| Storage encryption is turned off | Amazon RDS supports encryption at rest for all the database engines by using the keys that you manage in AWS Key Management Service (AWS KMS). On an active DB instance with Amazon RDS encryption, the data stored at rest in the storage is encrypted, similar to automated backups, read replicas, and snapshots. If encryption isn't turned on while creating a DB instance, you will need to create and restore an encrypted copy of the decrypted snapshot of the DB instance before you turn on the encryption. | Turn on encryption of data at rest for your DB instance. | Yes | [Security in Amazon RDS ](UsingWithRDS.md) [Copying a DB snapshot for Amazon RDS](USER_CopySnapshot.md) |
| Performance Insights is turned off | Performance Insights monitors your DB instance load to help you analyze and resolve database performance issues. We recommend that you turn on Performance Insights. | Turn on Performance Insights. | No | [Monitoring DB load with Performance Insights on Amazon RDS](USER_PerfInsights.md) |
| DB instances have storage autoscaling turned off | Storage autoscaling isn't turned on for your DB instance. When the database workload increases, RDS storage autoscaling automatically scales the storage capacity with zero downtime. | Turn on Amazon RDS storage autoscaling with a specified maximum storage threshold | No | [Managing capacity automatically with Amazon RDS storage autoscaling](USER_PIOPS.Autoscaling.md) |
| RDS resources major versions update is required | Databases with the current major version for the DB engine won't be supported. We recommend that you upgrade to the latest major version which includes new functionality and enhancements. | Upgrade to the latest major version for the DB engine. | Yes | [Upgrading a DB instance engine version](USER_UpgradeDBInstance.Upgrading.md) [Using Amazon RDS Blue/Green Deployments for database updates](blue-green-deployments.md) |
| RDS resources instance class update is required | Your DB instance is running an earlier generation DB instance class. We have replaced DB instance classes from an earlier generation with DB instance classes with better cost, performance, or both. We recommend that you run your DB instance with a DB instance class from a newer generation. | Upgrade the DB instance class. | Yes | [Supported DB engines for DB instance classes](Concepts.DBInstanceClass.Support.md) |
| RDS resources using end of support engine edition under license-included | We recommend that you upgrade the major version to the latest engine version supported by Amazon RDS to continue with the current license support. The engine version of your database won't be supported with the current license. | We recommend that you upgrade your database to the latest supported version in Amazon RDS to continue using the licensed model. | Yes | [Oracle major version upgrades](USER_UpgradeDBInstance.Oracle.Major.md) |
| DB instances not using Multi-AZ deployment | We recommend that you use Multi-AZ deployment. The Multi-AZ deployments enhance the availability and durability of the DB instance. | Set up Multi-AZ for the impacted DB instances | No Downtime doesn't occur during this change. However, there is a possible performance impact. For more information, see [Converting a DB instance to a Multi-AZ deployment for Amazon RDS](Concepts.MultiAZ.Migrating.md) | [Pricing for Amazon RDS Multi-AZ](https://aws.amazon.com/rds/features/multi-az/#Pricing) |
| DB memory parameters are diverging from default | The memory parameters of the DB instances are significantly different from the default values. These settings can impact performance and cause errors. We recommend that you reset the custom memory parameters for the DB instance to their default values in the DB parameter group. | Reset the memory parameters to their default values. | No | [ Best practices for configuring performance parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-1-parameters-related-to-performance/) on the AWS Database Blog |
| `InnoDB_Change_Buffering` parameter using less than optimum value | Change buffering allows a MySQL DB instance to defer a few writes, which are required to maintain secondary indexes. This feature was useful in environments with slow disks. The change buffering configuration improved the DB performance slightly but caused a delay in crash recovery and long shutdown times during upgrade. Set to `OFF` by default in MySQL version 8.4. | Set `InnoDB_Change_Buffering` parameter value to `NONE` in your DB parameter groups. | No | [ Best practices for configuring performance parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-1-parameters-related-to-performance/) on the AWS Database Blog |
| Query cache parameter is turned on | When changes require that your query cache is purged, your DB instance will appear to stall. Most workloads don't benefit from a query cache. The query cache was removed from MySQL 8.0 and higher versions. We recommend that you set the query\$1cache\$1type parameter to 0. | Set the `query_cache_type` parameter value to `0` in your DB parameter groups. | Yes | [ Best practices for configuring performance parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-1-parameters-related-to-performance/) on the AWS Database Blog |
| `log_output` parameter is set to table | When `log_output` is set to `TABLE`, more storage is used than when `log_output` is set to `FILE`. We recommend that you set the parameter to `FILE`, to avoid reaching the storage size limit. Set to `FILE` by default in MySQL 8.4 and higher versions. | Set the `log_output` parameter value to `FILE` in your DB parameter groups. | No | [MySQL database log files](USER_LogAccess.Concepts.MySQL.md) |
| Parameter groups not using huge pages | Large pages can increase database scalability, but your DB instance isn't using large pages. We recommend that you set the `use_large_pages` parameter value to `ONLY` in the DB parameter group for your DB instance. | Set the `use_large_pages` parameter value to `ONLY` in your DB parameter groups. | Yes | [Turning on HugePages for an RDS for Oracle instance](Oracle.Concepts.HugePages.md) |
| `autovacuum` parameter is turned off | The autovacuum parameter is turned off for your DB instances. Turning autovacuum off increases the table and index bloat and impacts the performance. We recommend that you turn on autovacuum in your DB parameter groups. | Turn on the autovacuum parameter in your DB parameter groups. | No | [ Understanding autovacuum in Amazon RDS for PostgreSQL environments](https://aws.amazon.com/blogs/database/understanding-autovacuum-in-amazon-rds-for-postgresql-environments/) on the AWS Database Blog |
| `synchronous_commit` parameter is turned off | When `synchronous_commit` parameter is turned off, data can be lost in a database crash. The durability of the database is at risk. We recommend that you turn on the `synchronous_commit` parameter. | Turn on `synchronous_commit` parameter in your DB parameter groups. | Yes | [ Amazon Aurora PostgreSQL parameters: Replication, security, and logging](https://aws.amazon.com/blogs/database/amazon-aurora-postgresql-parameters-part-2-replication-security-and-logging/) on the AWS Database Blog |
| `track_counts` parameter is turned off | When the `track_counts` parameter is turned off, the database doesn't collect the database activity statistics. Autovacuum requires these statistics to work correctly. We recommend that you set `track_counts` parameter to `1`. | Set `track_counts` parameter to `1`. | No | [Run-time Statistics for PostgreSQL](https://www.postgresql.org/docs/current/runtime-config-statistics.html#GUC-TRACK-COUNTS) |
| `enable_indexonlyscan` parameter is turned off | The query planner or optimizer can't use the index-only scan plan type when it is turned off. We recommend that you set the `enable_indexonlyscan` parameter value to `1`. | Set the `enable_indexonlyscan` parameter value to `1`. | No | [Planner Method Configuration for PostgreSQL](https://www.postgresql.org/docs/current/runtime-config-query.html#GUC-ENABLE-INDEXONLYSCAN) |
| `enable_indexscan` parameter is turned off | The query planner or optimizer can't use the index scan plan type when it is turned off. We recommend that you set the `enable_indexscan` value to `1`. | Set the `enable_indexscan` parameter value to `1`. | No | [Planner Method Configuration for PostgreSQL](https://www.postgresql.org/docs/current/runtime-config-query.html#GUC-ENABLE-INDEXONLYSCAN) |
| `innodb_flush_log_at_trx` parameter is turned off | The value of the `innodb_flush_log_at_trx` parameter of your DB instance isn't safe value. This parameter controls the persistence of commit operations to disk. We recommend that you set the `innodb_flush_log_at_trx` parameter to `1`. | Set the `innodb_flush_log_at_trx` parameter value to `1`. | No | [ Best practices for configuring performance parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-1-parameters-related-to-performance/) on the AWS Database Blog |
| `sync_binlog` parameter is turned off | The synchronization of the binary log to disk isn't enforced before the transaction commits are acknowledged in your DB instance. We recommend that you set the `sync_binlog` parameter value to `1`. | Set the `sync_binlog` parameter value to `1`. | No | [ Best practices for configuring replication parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-1-parameters-related-to-performance/) on the AWS Database Blog |
| `innodb_stats_persistent` parameter is turned off | Your DB instance isn't configured to persist the InnoDB statistics to the disk. When the statistics aren't stored, they are recalculated each time the instance restarts and the table accessed. This leads to variations in the query execution plan. You can modify the value of this global parameter at the table level. We recommend that you set the `innodb_stats_persistent` parameter value to `ON`. | Set the `innodb_stats_persistent` parameter value to `ON`. | No | [ Best practices for configuring performance parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-1-parameters-related-to-performance/) on the AWS Database Blog |
| `innodb_open_files` parameter is low | The `innodb_open_files` parameter controls the number of files InnoDB can open at one time. InnoDB opens all of the log and system tablespace files when mysqld is running. Your DB instance has a low value for the maximum number of files InnoDB can open at one time. We recommend that you set the `innodb_open_files` parameter to a minimum value of `65`. | Set the `innodb_open_files` parameter to a minimum value of `65`. | Yes | [InnoDB open files for MySQL](https://dev.mysql.com/doc/refman/5.7/en/innodb-parameters.html#sysvar_innodb_open_files) |
| `max_user_connections` parameter is low | Your DB instance has a low value for the maximum number of simultaneous connections for each database account. We recommend setting the `max_user_connections` parameter to a number greater than `5`. | Increase the value of the `max_user_connections` parameter to a number greater than `5`. | Yes | [Setting Account Resource Limits for MySQL](https://dev.mysql.com/doc/refman/8.0/en/user-resources.html) |
| Read Replicas are open in writable mode | Your DB instance has a read replica in writable mode, which allows updates from clients. We recommend that you set the `read_only` parameter to `TrueIfReplica` so that the read replicas isn't in writable mode. | Set the `read_only` parameter value to `TrueIfReplica`. | No | [ Best practices for configuring replication parameters for Amazon RDS for MySQL](https://aws.amazon.com/blogs/database/best-practices-for-configuring-parameters-for-amazon-rds-for-mysql-part-2-parameters-related-to-replication/) on the AWS Database Blog |
| `innodb_default_row_format` parameter setting is unsafe | Your DB instance encounters a known issue: A table created in a MySQL version lower than 8.0.26 with the `row_format` set to `COMPACT` or `REDUNDANT` will be inaccessible and unrecoverable when the index exceeds 767 bytes. We recommend that you set the `innodb_default_row_format` parameter value to `DYNAMIC`. | Set the `innodb_default_row_format` parameter value to `DYNAMIC`. | No | [ Changes in MySQL 8.0.26](https://dev.mysql.com/doc/relnotes/mysql/8.0/en/news-8-0-26.html#mysqld-8-0-26-bug) |
| `general_logging` parameter is turned on | The general logging is turned on for your DB instance. This setting is useful while troubleshooting the database issues. However, turning on general logging increases the amount of I/O operations and allocated storage space, which might result in contention and performance degradation. Check your requirements for general logging usage. We recommend that you set the `general_logging` parameter value to `0`. | Check your requirements for general logging usage. If it isn't mandatory, we recommend that you to set the `general_logging` parameter value to `0`. | No | [Overview of RDS for MySQL database logs](USER_LogAccess.MySQL.LogFileSize.md) |
| RDS instance under-provisioned for system memory capacity | We recommend that you tune your queries to use lesser memory or use a DB instance type with higher allocated memory. When the instance is running low on memory, then the database performance is impacted. | Use a DB instance with higher memory capacity | Yes | [ Scaling Your Amazon RDS Instance Vertically and Horizontally](https://aws.amazon.com/blogs/database/scaling-your-amazon-rds-instance-vertically-and-horizontally/) on the AWS Database Blog [Amazon RDS instance types](https://aws.amazon.com/rds/instance-types/) [Amazon RDS pricing](https://aws.amazon.com/rds/pricing/) |
| RDS instance under-provisioned for system CPU capacity | We recommend that you tune your queries to use less CPU or modify your DB instance to use a DB instance class with higher allocated vCPUs. Database performance might decline when a DB instance is running low on CPU. | Use a DB instance with higher CPU capacity | Yes | [ Scaling Your Amazon RDS Instance Vertically and Horizontally](https://aws.amazon.com/blogs/database/scaling-your-amazon-rds-instance-vertically-and-horizontally/) on the AWS Database Blog [Amazon RDS instance types](https://aws.amazon.com/rds/instance-types/) [Amazon RDS pricing](https://aws.amazon.com/rds/pricing/) |
| RDS resources are not utilizing connection pooling correctly | We recommend that you enable Amazon RDS Proxy to efficiently pool and share existing database connections. If you are already using a proxy for your database, configure it correctly to improve connection pooling and load balancing across multiple DB instances. RDS Proxy can help reduce the risk of connection exhaustion and downtime while improving availability and scalability. | Enable RDS Proxy or modify your existing proxy configuration | No | [ Scaling Your Amazon RDS Instance Vertically and Horizontally](https://aws.amazon.com/blogs/database/scaling-your-amazon-rds-instance-vertically-and-horizontally/) on the AWS Database Blog [Amazon RDS Proxy](rds-proxy.md) [Amazon RDS Proxy Pricing](https://aws.amazon.com/rds/proxy/pricing/) |
| RDS instances are creating excessive temporary objects | We recommend that you tune your workload to prevent creating excessive temporary objects, or switch to RDS instance classes supporting optimized reads. RDS Optimized Reads improves database performance for workloads involving a large number of temporary objects and/or large temporary objects. Evaluate your workload to determine if using an instance with RDS Optimized Reads benefits your database workload. | Use a DB instance type with RDS Optimized Reads | Yes | [Amazon RDS instance types](https://aws.amazon.com/rds/instance-types/) [Improving query performance for RDS for MySQL with Amazon RDS Optimized Reads](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-optimized-reads.html) [Improving query performance for RDS for MariaDB with Amazon RDS Optimized Reads](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-optimized-reads-mariadb.html) [Improving query performance for RDS for PostgreSQL with Amazon RDS Optimized Reads](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PostgreSQL.optimizedreads.html) |
| RDS instances are under-provisioned for system IOPS capacity | We recommend tuning the database workload to reduce IOPS or scale up the DB instance to a type with a higher default IOPS limit. The current DB instance can't support the Provisioned IOPS, or the database workload has high IOPS utilization. | Use a DB instance type with higher default IOPS limits | Yes | [Amazon RDS instance types](https://aws.amazon.com/rds/instance-types/) [Amazon RDS DB instance storage](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html) [Database load](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.ActiveSessions.html) |
| RDS instances have under-provisioned Amazon EBS volumes | We recommend tuning the database workload to reduce IOPS or increase the Provisioned IOPS for the database. When IOPS utilization approaches the Provisioned IOPS, database performance might decline. | Provision more IOPS for the DB instance | Yes | [Amazon RDS instance types](https://aws.amazon.com/rds/instance-types/) [Amazon RDS DB instance storage](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html) [Database load](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.ActiveSessions.html) |
| RDS instances are under-provisioned for throughput capacity | We recommend tuning the database workload to reduce throughput or increase the provisioned throughput for the database. When throughput utilization approaches the provisioned throughput, database performance might be impacted. | Provision more throughput for the DB instance | Yes | [Amazon RDS instance types](https://aws.amazon.com/rds/instance-types/) [Amazon RDS DB instance storage](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html) [Database load](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.ActiveSessions.html) |
| RDS instances are under-provisioned for EBS I/O | We recommend tuning the database workload to reduce I/O operations or modifying the DB instance to use Amazon RDS io2 Block Express volumes which are designed for database workloads that require high performance, high throughput, and low latency. With the current workload, the database might not be able to process I/O operations at the required rate which can lead to performance degradation. | Use Amazon RDS io2 Block Express volumes for the RDS instance | No | [Amazon RDS DB instance storage](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/CHAP_Storage.html) [Amazon CloudWatch metrics for Amazon RDS](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-metrics.html) [Provisioned IOPS SSD volumes](https://docs.aws.amazon.com/ebs/latest/userguide/provisioned-iops.html) in the Amazon EBS User Guide |
# Viewing metrics in the Amazon RDS console
Amazon RDS integrates with Amazon CloudWatch to display a variety of RDS DB instance metrics in the RDS console. For descriptions of these metrics, see [Metrics reference for Amazon RDS](metrics-reference.md).
For your DB instance, the following categories of metrics are monitored:
+ **CloudWatch** – Shows the Amazon CloudWatch metrics for RDS that you can access in the RDS console. You can also access these metrics in the CloudWatch console. Each metric includes a graph that shows the metric monitored over a specific time span. For a list of CloudWatch metrics, see [Amazon CloudWatch metrics for Amazon RDS](rds-metrics.md).
+ **Enhanced monitoring** – Shows a summary of operating-system metrics when your RDS DB instance has turned on Enhanced Monitoring. RDS delivers the metrics from Enhanced Monitoring to your Amazon CloudWatch Logs account. Each OS metric includes a graph showing the metric monitored over a specific time span. For an overview, see [Monitoring OS metrics with Enhanced Monitoring](USER_Monitoring.OS.md). For a list of Enhanced Monitoring metrics, see [OS metrics in Enhanced Monitoring](USER_Monitoring-Available-OS-Metrics.md).
+ **OS Process list** – Shows details for each process running in your DB instance.
+ **Performance Insights** – Opens the Amazon RDS Performance Insights dashboard for a DB instance. For an overview of Performance Insights, see [Monitoring DB load with Performance Insights on Amazon RDS](USER_PerfInsights.md). For a list of Performance Insights metrics, see [Amazon CloudWatch metrics for Amazon RDS Performance Insights](USER_PerfInsights.Cloudwatch.md).
Amazon RDS now provides a consolidated view of Performance Insights and CloudWatch metrics in the Performance Insights dashboard. Performance Insights must be turned on for your DB instance to use this view. You can choose the new monitoring view in the **Monitoring** tab or **Performance Insights** in the navigation pane. To view the instructions for choosing this view, see [Viewing combined metrics with the Performance Insights dashboard](Viewing_Unifiedmetrics.md).
# Viewing combined metrics with the Performance Insights dashboard
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
Amazon RDS provides a consolidated view of Performance Insights and CloudWatch metrics for your DB instance in the Performance Insights dashboard. You can use the preconfigured dashboard or create a custom dashboard. The preconfigured dashboard provides the most commonly used metrics to help diagnose performance issues for a database engine. Alternatively, you can create a custom dashboard with the metrics for a database engine that meet your analysis requirements. Then, use this dashboard for all the DB instances of that database engine type in your AWS account.
You can choose the monitoring view in the **Monitoring** tab or **Performance Insights** in the navigation pane.
Performance Insights must be turned on for your DB instance to view the combined metrics in the Performance Insights dashboard. For more information about turning on Performance Insights, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md).
In the following sections, you can learn to display Performance Insights and CloudWatch metrics.
**Topics**
+ [
# Choosing the new monitoring view from the Monitoring tab
](Viewing_Unifiedmetrics.MonitoringTab.md)
+ [
# Choosing the new monitoring view from the Performance Insights page
](Viewing_Unifiedmetrics.PInavigationPane.md)
+ [
# Creating a custom dashboard with Performance Insights
](Viewing_Unifiedmetrics.PIcustomizeMetricslist.md)
+ [
# Choosing the preconfigured dashboard with Performance Insights
](Viewing_Unifiedmetrics.PI-preconfigured-dashboard.md)
# Choosing the new monitoring view from the Monitoring tab
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
From the Amazon RDS console, you can choose the new monitoring view to view Performance Insights and CloudWatch metrics for your DB instance.
**To choose the new monitoring view in the Monitoring tab**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Databases**.
1. Choose the DB instance that you want to monitor.
1. Scroll down and choose the **Monitoring** tab.
A banner appears with the option to choose the new monitoring view. The following example shows the banner to choose the new monitoring view.
![\[Banner with navigation to new monitoring view.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/NewMonitoringViewOption.png)
1. Choose **Go to new monitoring view** to open the Performance Insights dashboard with Performance Insights and CloudWatch metrics for your DB instance.
1. (Optional) If Performance Insights is turned off for your DB instance, a banner appears with the option to modify your DB cluster and turn on Performance Insights.
The following example shows the banner to modify the DB cluster in the **Monitoring** tab .
![\[Modify DB instance to turn on Performance Insights.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Monitoring_modifyInstnc_banner.png)
Choose **Modify** to modify your DB cluster and turn on Performance Insights. For more information about turning on Performance Insights, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md)
# Choosing the new monitoring view from the Performance Insights page
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
From the Amazon RDS console, you can choose the new monitoring view to view Performance Insights and CloudWatch metrics for your DB instance.
**To choose the new monitoring view with Performance Insights in the navigation pane**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance to view the Performance Insights dashboard that shows both Performance Insights and CloudWatch metrics for your DB instance.
![\[Consolidated Performance Insights and CloudWatch metrics dashboard.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Monitoring_UnifiedDashboard.png)
# Creating a custom dashboard with Performance Insights
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
In the new monitoring view, you can create a custom dashboard with the metrics you need to meet your analysis requirements.
You can create a custom dashboard by selecting Performance Insights and CloudWatch metrics for your DB instance. You can use this custom dashboard for other DB instances of the same database engine type in your AWS account.
**Note**
The customized dashboard supports up to 50 metrics.
Use the widget settings menu to edit or delete the dashboard, and move or resize the widget window.
**To create a custom dashboard with Performance Insights in the navigation pane**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
1. Scroll down to the **Metrics tab** in the window.
1. Select the custom dashboard from the drop down list. The following example shows the custom dashboard creation.
![\[Custom metrics dashboard with no widgets yet.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Monitoring_custmDashbrd_addWidget.png)
1. Choose **Add widget** to open the **Add widget** window. You can open and view the available operating system (OS) metrics, database metrics, and CloudWatch metrics in the window.
The following example shows the **Add widget** window with the metrics.
![\[The metrics options in the Add Widget window.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Monitoring_AddWidget.png)
1. Select the metrics that you want to view in the dashboard and choose **Add widget**. You can use the search field to find a specific metric.
The selected metrics appear on your dashboard.
1. (Optional) If you want to modify or delete your dashboard, choose the settings icon on the upper right of the widget, and then select one of the following actions in the menu.
+ **Edit** – Modify the metrics list in the window. Choose **Update widget** after you select the metrics for your dashboard.
+ **Delete** – Deletes the widget. Choose **Delete** in the confirmation window.
# Choosing the preconfigured dashboard with Performance Insights
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
You can view the most commonly used metrics with the preconfigured dashboard. This dashboard helps diagnose performance issues with a database engine and reduce the average recovery time from hours to minutes.
**Note**
This dashboard can't be edited.
**To choose the preconfigured dashboard with Performance Insights in the navigation pane**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
1. Scroll down to the **Metrics tab** in the window
1. Select a preconfigured dashboard from the drop down list.
You can view the metrics for the DB instance in the dashboard. The following example shows a preconfigured metrics dashboard.
![\[Preconfigured metrics dashboard.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Monitoring_preconfigDashboard.png)
# Monitoring Amazon RDS metrics with Amazon CloudWatch
Amazon CloudWatch is a metrics repository. The repository collects and processes raw data from Amazon RDS into readable, near real-time metrics. For a complete list of Amazon RDS metrics sent to CloudWatch, see [ Metrics reference for Amazon RDS](https://docs.aws.amazon.com/en_us/AmazonRDS/latest/UserGuide/metrics-reference.html).
To analyze and troubleshoot the performance of your databases at scale, use [CloudWatch Database Insights](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_DatabaseInsights.html).
**Topics**
+ [
## Overview of Amazon RDS and Amazon CloudWatch
](#cw-metrics-overview)
+ [
# Viewing DB instance metrics in the CloudWatch console and AWS CLI
](metrics_dimensions.md)
+ [
# Exporting Performance Insights metrics to CloudWatch
](PI_metrics_export_CW.md)
+ [
# Creating CloudWatch alarms to monitor Amazon RDS
](creating_alarms.md)
+ [
# Tutorial: Creating an Amazon CloudWatch alarm for Multi-AZ DB cluster replica lag for Amazon RDS
](multi-az-db-cluster-cloudwatch-alarm.md)
## Overview of Amazon RDS and Amazon CloudWatch
By default, Amazon RDS automatically sends metric data to CloudWatch in 1-minute periods. For example, the `CPUUtilization` metric records the percentage of CPU utilization for a DB instance over time. Data points with a period of 60 seconds (1 minute) are available for 15 days. This means that you can access historical information and see how your web application or service is performing.
You can now export Performance Insights metrics dashboards from Amazon RDS to Amazon CloudWatch. You can export either the preconfigured or customized metrics dashboards as a new dashboard or add them to an existing CloudWatch dashboard. The exported dashboard is available to view in the CloudWatch console. For more information on how to export the Performance Insights metrics dashboards to CloudWatch, see [Exporting Performance Insights metrics to CloudWatch](PI_metrics_export_CW.md).
As shown in the following diagram, you can set up alarms for your CloudWatch metrics. For example, you might create an alarm that signals when the CPU utilization for an instance is over 70%. You can configure Amazon Simple Notification Service to email you when the threshold is passed.
![\[RDS metrics in AWS CloudWatch\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/rds-cloudwatch.png)
Amazon RDS publishes the following types of metrics to Amazon CloudWatch:
+ Metrics for your RDS DB instances
For a table of these metrics, see [Amazon CloudWatch metrics for Amazon RDS](rds-metrics.md).
+ Performance Insights metrics
For a table of these metrics, see [Amazon CloudWatch metrics for Amazon RDS Performance Insights](USER_PerfInsights.Cloudwatch.md) and [Performance Insights counter metrics](USER_PerfInsights_Counters.md).
+ Enhanced Monitoring metrics (published to Amazon CloudWatch Logs)
For a table of these metrics, see [OS metrics in Enhanced Monitoring](USER_Monitoring-Available-OS-Metrics.md).
+ Usage metrics for the Amazon RDS service quotas in your AWS account
For a table of these metrics, see [Amazon CloudWatch usage metrics for Amazon RDS](rds-metrics.md#rds-metrics-usage). For more information about Amazon RDS quotas, see [Quotas and constraints for Amazon RDS](CHAP_Limits.md).
For more information about CloudWatch, see [ What is Amazon CloudWatch?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/WhatIsCloudWatch.html) in the *Amazon CloudWatch User Guide*. For more information about CloudWatch metrics retention, see [Metrics retention](https://docs.aws.amazon.com/AmazonCloudWatch/latest/DeveloperGuide/cloudwatch_concepts.html#metrics-retention).
# Viewing DB instance metrics in the CloudWatch console and AWS CLI
Following, you can find details about how to view metrics for your DB instance using CloudWatch. For information on monitoring metrics for your DB instance's operating system in real time using CloudWatch Logs, see [Monitoring OS metrics with Enhanced Monitoring](USER_Monitoring.OS.md).
When you use Amazon RDS resources, Amazon RDS sends metrics and dimensions to Amazon CloudWatch every minute.
You can now export Performance Insights metrics dashboards from Amazon RDS to Amazon CloudWatch and view these metrics in the CloudWatch console. For more information on how to export the Performance Insights metrics dashboards to CloudWatch, see [Exporting Performance Insights metrics to CloudWatch](PI_metrics_export_CW.md).
Use the following procedures to view the metrics for Amazon RDS in the CloudWatch console and CLI.
## Console
**To view metrics using the Amazon CloudWatch console**
Metrics are grouped first by the service namespace, and then by the various dimension combinations within each namespace.
1. Open the CloudWatch console at [https://console.aws.amazon.com/cloudwatch/](https://console.aws.amazon.com/cloudwatch/).
The CloudWatch overview home page appears.
![\[CloudWatch overview page\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/monitoring-overviewpage-console2.png)
1. If necessary, change the AWS Region. From the navigation bar, choose the AWS Region where your AWS resources are. For more information, see [Regions and endpoints](https://docs.aws.amazon.com/general/latest/gr/rande.html).
1. In the navigation pane, choose **Metrics** and then **All metrics**.
![\[Choose metric namespace\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/cw-all-metrics.png)
1. Scroll down and choose the **RDS** metric namespace.
The page displays the Amazon RDS dimensions. For descriptions of these dimensions, see [Amazon CloudWatch dimensions for Amazon RDS](dimensions.md).
![\[Choose metric namespace\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/rds-monitoring-01.png)
1. Choose a metric dimension, for example **By Database Class**.
![\[Filter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/metrics-by-instance-class.png)
1. Do any of the following actions:
+ To sort the metrics, use the column heading.
+ To graph a metric, select the check box next to the metric.
+ To filter by resource, choose the resource ID, and then choose **Add to search**.
+ To filter by metric, choose the metric name, and then choose **Add to search**.
The following example filters on the **db.t3.medium** class and graphs the **CPUUtilization** metric.
![\[Filter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/rds-monitoring-03.png)
## AWS CLI
To obtain metric information by using the AWS CLI, use the CloudWatch command [https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/list-metrics.html](https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/list-metrics.html). In the following example, you list all metrics in the `AWS/RDS` namespace.
```
aws cloudwatch list-metrics --namespace AWS/RDS
```
To obtain metric data, use the command [https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/get-metric-data.html](https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/get-metric-data.html).
The following example gets `CPUUtilization` statistics for instance `my-instance` over the specific 24-hour period, with a 5-minute granularity.
Create a JSON file `CPU_metric.json` with the following contents.
```
1. {
2. "StartTime" : "2023-12-25T00:00:00Z",
3. "EndTime" : "2023-12-26T00:00:00Z",
4. "MetricDataQueries" : [{
5. "Id" : "cpu",
6. "MetricStat" : {
7. "Metric" : {
8. "Namespace" : "AWS/RDS",
9. "MetricName" : "CPUUtilization",
10. "Dimensions" : [{ "Name" : "DBInstanceIdentifier" , "Value" : my-instance}]
11. },
12. "Period" : 360,
13. "Stat" : "Minimum"
14. }
15. }]
16. }
```
**Example**
For Linux, macOS, or Unix:
```
1. aws cloudwatch get-metric-data \
2. --cli-input-json file://CPU_metric.json
```
For Windows:
```
1. aws cloudwatch get-metric-data ^
2. --cli-input-json file://CPU_metric.json
```
Sample output appears as follows:
```
{
"MetricDataResults": [
{
"Id": "cpu",
"Label": "CPUUtilization",
"Timestamps": [
"2023-12-15T23:48:00+00:00",
"2023-12-15T23:42:00+00:00",
"2023-12-15T23:30:00+00:00",
"2023-12-15T23:24:00+00:00",
...
],
"Values": [
13.299778337027714,
13.677507543049558,
14.24976250395827,
13.02521708695145,
...
],
"StatusCode": "Complete"
}
],
"Messages": []
}
```
For more information, see [Getting statistics for a metric](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/getting-metric-data.html) in the *Amazon CloudWatch User Guide*.
# Exporting Performance Insights metrics to CloudWatch
Performance Insights lets you export the preconfigured or custom metrics dashboard for your DB instance to Amazon CloudWatch. You can export the metrics dashboard as a new dashboard or add it to an existing CloudWatch dashboard. When you choose to add the dashboard to an existing CloudWatch dashboard, you can create a header label so that the metrics appear in a separate section in the CloudWatch dashboard.
You can view the exported metrics dashboard in the CloudWatch console. If you add new metrics to a Performance Insights metrics dashboard after you export it, you must export this dashboard again to view the new metrics in the CloudWatch console.
You can also select a metric widget in the Performance Insights dashboard and view the metrics data in the CloudWatch console.
For more information about viewing the metrics in the CloudWatch console, see [Viewing DB instance metrics in the CloudWatch console and AWS CLI](metrics_dimensions.md).
In the following sections, export Performance Insights metrics to CloudWatch as a new or existing dashboard and view Performance Insights metrics in CloudWatch.
**Topics**
+ [
# Exporting Performance Insights metrics as a new dashboard to CloudWatch
](PI_metrics_export_CW.new_dashboard.md)
+ [
# Adding Performance Insights metrics to an existing CloudWatch dashboard
](PI_metrics_export_CW.existing_dashboard.md)
+ [
# Viewing a Performance Insights metric widget in CloudWatch
](PI_metrics_export_CW.individual_widget.md)
# Exporting Performance Insights metrics as a new dashboard to CloudWatch
Choose a preconfigured or custom metrics dashboard from the Performance Insights dashboard and export it as a new dashboard to CloudWatch. You can view the exported dashboard in the CloudWatch console.
**To export a Performance Insights metric dashboard as a new dashboard to CloudWatch**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
The Performance Insights dashboard appears for the DB instance.
1. Scroll down and choose **Metrics**.
By default, the preconfigured dashboard with Performance Insights metrics appears.
1. Choose a preconfigured or custom dashboard and then choose **Export to CloudWatch**.
The **Export to CloudWatch** window appears.
![\[Performance Insights dashboard with export to CloudWatch button\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI-ExprtToCW.png)
1. Choose **Export as new dashboard**.
![\[Export to CloudWatch window with export as new dashboard option selected\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI-ExprtToCW-NewDashboard.png)
1. Enter a name for the new dashboard in the **Dashboard name** field and choose **Confirm**.
A banner displays a message after the dashboard export is successful.
![\[Banner with successful message\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI-ExprtToCW-SuccessBanner.png)
1. Choose the link or **View in CloudWatch** in the banner to view the metrics dashboard in the CloudWatch console.
# Adding Performance Insights metrics to an existing CloudWatch dashboard
Add a preconfigured or custom metrics dashboard to an existing CloudWatch dashboard. You can add a label to the metrics dashboard to appear in a separate section in the CloudWatch dashboard.
**To export the metrics to an existing CloudWatch dashboard**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
The Performance Insights dashboard appears for the DB instance.
1. Scroll down and choose **Metrics**.
By default, the preconfigured dashboard with Performance Insights metrics appears.
1. Choose the preconfigured or custom dashboard and then choose **Export to CloudWatch**.
The **Export to CloudWatch** window appears.
1. Choose **Add to existing dashboard**.
![\[Export to CloudWatch window with add to existing dashboard option selected\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/Pi-ExprtToCW-AddToExistingBoard.png)
1. Specify the dashboard destination and label, and then choose **Confirm**.
+ **CloudWatch dashboard destination** - Choose an existing CloudWatch dashboard.
+ **CloudWatch dashboard section label - optional** - Enter a name for the Performance Insights metrics to appear in this section in the CloudWatch dashboard.
A banner displays a message after the dashboard export is successful.
1. Choose the link or **View in CloudWatch** in the banner to view the metrics dashboard in the CloudWatch console.
# Viewing a Performance Insights metric widget in CloudWatch
Select a Performance Insights metric widget in the Amazon RDS Performance Insights dashboard and view the metric data in the CloudWatch console.
**To export a metric widget and view the metrics data in the CloudWatch console**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
The Performance Insights dashboard appears for the DB instance.
1. Scroll down to **Metrics**.
By default, the preconfigured dashboard with Performance Insights metrics appears.
1. Choose a metric widget and then choose **View in CloudWatch** in the menu.
![\[Selected widget with menu to view in CloudWatch\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI-ExprtToCW-SelectedMetric.png)
The metric data appears in the CloudWatch console.
# Creating CloudWatch alarms to monitor Amazon RDS
You can create a CloudWatch alarm that sends an Amazon SNS message when the alarm changes state. An alarm watches a single metric over a time period that you specify. The alarm can also perform one or more actions based on the value of the metric relative to a given threshold over a number of time periods. The action is a notification sent to an Amazon SNS topic or Amazon EC2 Auto Scaling policy.
Alarms invoke actions for sustained state changes only. CloudWatch alarms don't invoke actions simply because they are in a particular state. The state must have changed and have been maintained for a specified number of time periods.
You can use the **DB\$1PERF\$1INSIGHTS** metric math function in the CloudWatch console to query Amazon RDS for Performance Insights counter metrics. The **DB\$1PERF\$1INSIGHTS** function also includes the DBLoad metric at sub-minute intervals. You can set CloudWatch alarms on these metrics.
For more details on how to create an alarm, see [ Create an alarm on Performance Insights counter metrics from an AWS database](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_alarm_database_performance_insights.html).
**To set an alarm using the AWS CLI**
+ Call [https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/put-metric-alarm.html](https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/put-metric-alarm.html). For more information, see *[AWS CLI Command Reference](https://docs.aws.amazon.com/cli/latest/reference/)*.
**To set an alarm using the CloudWatch API**
+ Call [https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_PutMetricAlarm.html](https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/API_PutMetricAlarm.html). For more information, see *[Amazon CloudWatch API Reference](https://docs.aws.amazon.com/AmazonCloudWatch/latest/APIReference/)*
For more information about setting up Amazon SNS topics and creating alarms, see [Using Amazon CloudWatch alarms](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/AlarmThatSendsEmail.html).
# Tutorial: Creating an Amazon CloudWatch alarm for Multi-AZ DB cluster replica lag for Amazon RDS
You can create an Amazon CloudWatch alarm that sends an Amazon SNS message when replica lag for a Multi-AZ DB cluster has exceeded a threshold. An alarm watches the `ReplicaLag` metric over a time period that you specify. The action is a notification sent to an Amazon SNS topic or Amazon EC2 Auto Scaling policy.
**To set a CloudWatch alarm for Multi-AZ DB cluster replica lag**
1. Sign in to the AWS Management Console and open the CloudWatch console at [https://console.aws.amazon.com/cloudwatch/](https://console.aws.amazon.com/cloudwatch/).
1. In the navigation pane, choose **Alarms**, **All alarms**.
1. Choose **Create alarm**.
1. On the **Specify metric and conditions** page, choose **Select metric**.
1. In the search box, enter the name of your Multi-AZ DB cluster and press Enter.
The following image shows the **Select metric** page with a Multi-AZ DB cluster named `rds-cluster` entered.
![\[Select metric page\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-select-metric.png)
1. Choose **RDS**, **Per-Database Metrics**.
1. In the search box, enter **ReplicaLag** and press Enter, then select each DB instance in the DB cluster.
The following image shows the **Select metric** page with the DB instances selected for the **ReplicaLag** metric.
![\[Select metric page with DB instances selected for the ReplicaLag metric\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-metric-replica-lag.png)
This alarm considers the replica lag for all three of the DB instances in the Multi-AZ DB cluster. The alarm responds when any DB instance exceeds the threshold. It uses a math expression that returns the maximum value of the three metrics. Start by sorting by metric name, and then choose all three **ReplicaLag** metrics.
1. From **Add math**, choose **All functions**, **MAX**.
![\[The Add math setting\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-select-metric-math.png)
1. Choose the **Graphed metrics** tab, and edit the details for **Expression1** to **MAX([m1,m2,m3])**.
1. For all three **ReplicaLag** metrics, change the **Period** to **1 minute**.
1. Clear selection from all metrics except for **Expression1**.
The **Select metric** page should look similar to the following image.
![\[The Select metric page with the metric selected\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-select-metric-expression1.png)
1. Choose **Select metric**.
1. On the **Specify metric and conditions** page, change the label to a meaningful name, such as **ClusterReplicaLag**, and enter a number of seconds in **Define the threshold value**. For this tutorial, enter **1200** seconds (20 minutes). You can adjust this value for your workload requirements.
The **Specify metric and conditions** page should look similar to the following image.
![\[The Specify metric and conditions page\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-specify-metric-conditions.png)
1. Choose **Next**, and the **Configure actions** page appears.
1. Keep **In alarm** selected, choose **Create new topic**, and enter the topic name and a valid email address.
![\[The Configure actions page\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-configure-actions.png)
1. Choose **Create topic**, and then choose **Next**.
1. On the **Add name and description** page, enter the **Alarm name** and **Alarm description**, and then choose **Next**.
![\[The Add name and description page\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/multi-az-db-cluster-cw-tutorial-add-name-and-description.png)
1. Preview the alarm that you're about to create on the **Preview and create** page, and then choose **Create alarm**.
# Monitoring Amazon RDS databases with CloudWatch Database Insights
Monitor the database load (DB Load) for your fleet of Amazon RDS DB instances with Database Insights. DB Load measures the level of session activity in your database. You can use Database Insights to analyze and troubleshoot the performance of your Amazon RDS databases at scale.
With Database Insights, you can visualize the DB Load on your fleet of databases and filter the load by waits, SQL statements, hosts, or users.
By default, RDS enables the Standard mode of Database Insights for your Amazon RDS databases.
For information about using Database Insights in the Amazon CloudWatch console, see [CloudWatch Database Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Database-Insights.html) in the *Amazon CloudWatch User Guide*.
## Pricing
For information about pricing, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
**Topics**
+ [
## Pricing
](#USER_Database-Insights-pricing)
+ [
# Amazon RDS DB engine, Region, and instance class support for Database Insights
](USER_DatabaseInsights.Engines.md)
+ [
# Turning on the Advanced mode of Database Insights for Amazon RDS
](USER_DatabaseInsights.TurningOnAdvanced.md)
+ [
# Turning on the Standard mode of Database Insights for Amazon RDS
](USER_DatabaseInsights.TurningOnStandard.md)
+ [
# Configuring your database to monitor slow SQL queries with Database Insights for Amazon RDS
](USER_DatabaseInsights.SlowSQL.md)
+ [
# Considerations for Database Insights for Amazon RDS
](USER_DatabaseInsights.Considerations.md)
# Amazon RDS DB engine, Region, and instance class support for Database Insights
The following table provides Amazon RDS DB engines that support Database Insights.
| Amazon RDS DB engine | Supported engine versions and Regions | Instance class restrictions |
| --- | --- | --- |
| Amazon RDS for MariaDB | For more information on version and Region availability of Database Insights with RDS for MariaDB, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | Database Insights isn't supported for the following instance classes: [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_DatabaseInsights.Engines.html) |
| RDS for MySQL | For more information on version and Region availability of Database Insights with RDS for MySQL, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | Database Insights isn't supported for the following instance classes: [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_DatabaseInsights.Engines.html) |
| Amazon RDS for Microsoft SQL Server | For more information on version and Region availability of Database Insights with RDS for SQL Server, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | N/A |
| Amazon RDS for PostgreSQL | For more information on version and Region availability of Database Insights with RDS for PostgreSQL, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | N/A |
| Amazon RDS for Oracle | For more information on version and Region availability of Database Insights with RDS for Oracle, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | N/A |
## Amazon RDS DB engine, Region, and instance class support for Database Insights features
The following table provides Amazon RDS DB engines that support Database Insights features.
| Feature | [Pricing tier](https://aws.amazon.com/rds/performance-insights/pricing/) | [Supported regions](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.RegionsAndAvailabilityZones.html#Concepts.RegionsAndAvailabilityZones.Regions) | [ Supported DB engines](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html#Welcome.Concepts.DBInstance) | [Supported instance classes](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.html#Concepts.DBInstanceClass.Types) |
| --- | --- | --- | --- | --- |
| [SQL statistics for Performance Insights](sql-statistics.md) | All | All | All | All |
| [Analyzing Oracle execution plans using the Performance Insights dashboard for Amazon RDS](USER_PerfInsights.UsingDashboard.AccessPlans.md) | All | All | RDS for Oracle | All |
| [Analyzing database performance for a period of time](USER_PerfInsights.UsingDashboard.AnalyzePerformanceTimePeriod.md) | Paid tier only | All | [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_DatabaseInsights.Engines.html) | All |
| [Viewing Performance Insights proactive recommendations](USER_PerfInsights.InsightsRecommendationViewDetails.md) | Paid tier only | [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_DatabaseInsights.Engines.html) | All | All |
## Amazon RDS Region support for Database Insights
Amazon RDS supports Database Insights in the following AWS Regions.
+ US East (N. Virginia)
+ US East (Ohio)
+ US West (N. California)
+ US West (Oregon)
+ Africa (Cape Town)
+ Asia Pacific (Hong Kong)
+ Asia Pacific (Hyderabad)
+ Asia Pacific (Jakarta)
+ Asia Pacific (Malaysia)
+ Asia Pacific (Melbourne)
+ Asia Pacific (Mumbai)
+ Asia Pacific (Osaka)
+ Asia Pacific (Seoul)
+ Asia Pacific (Singapore)
+ Asia Pacific (Sydney)
+ Asia Pacific (Tokyo)
+ Canada (Central)
+ Canada West (Calgary)
+ Europe (Frankfurt)
+ Europe (Ireland)
+ Europe (London)
+ Europe (Milan)
+ Europe (Paris)
+ Europe (Spain)
+ Europe (Stockholm)
+ Europe (Zurich)
+ Israel (Tel Aviv)
+ Middle East (Bahrain)
+ Middle East (UAE)
+ South America (São Paulo)
+ AWS GovCloud (US-East)
+ AWS GovCloud (US-West)
# Turning on the Advanced mode of Database Insights for Amazon RDS
To turn on the Advanced mode of Database Insights for Amazon RDS, use the following procedures.
## Turning on the Advanced mode of Database Insights when creating a DB instance or Multi-AZ DB cluster
Turn on the Advanced mode of Database Insights when creating a database for Amazon RDS.
------
#### [ Console ]
In the console, you can turn on the Advanced mode of Database Insights when you create a DB instance or Multi-AZ DB cluster.
**To turn on the Advanced mode of Database Insights when creating a DB instance or Multi-AZDB cluster using the console**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Databases**.
1. Choose **Create database**.
1. In the **Database Insights** section, select **Advanced mode**. Then, choose the following options:
+ **Retention** – The amount of time to retain Performance Insights data. The retention period must be 15 months for the Advanced mode of Database Insights.
+ **AWS KMS key** – Specify your KMS key. Performance Insights encrypts all potentially sensitive data using your KMS key. Data is encrypted in flight and at rest. For more information, see [Encrypting Amazon RDS resources](Overview.Encryption.md).
1. Choose **Create database**.
------
#### [ AWS CLI ]
To turn on the Advanced mode of Database Insights when creating a DB instance or Multi-AZ DB cluster, call the [create-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-instance.html) or [create-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-cluster.html) AWS CLI command and supply the following values:
+ `--database-insights-mode advanced` to turn on the Advanced mode of Database Insights.
+ `--engine` – The database engine for the DB instance.
+ `--db-instance-identifier` – The identifier for the DB instance or `--db-cluster-identifier` – The identifier for the Multi-AZ DB cluster.
+ `--enable-performance-insights` to turn on Performance Insights for Database Insights.
+ `--performance-insights-retention-period` – The retention period for data for your DB instance or Multi-AZ DB cluster. To turn on Database Insights, the retention period must be at least 465 days.
The following example enables the Advanced mode of Database Insights when creating a DB instance.
For Linux, macOS, or Unix:
```
aws rds create-db-instance \
--database-insights-mode advanced \
--engine postgresql \
--db-instance-identifier sample-db-identifier \
--enable-performance-insights \
--performance-insights-retention-period 465
```
For Windows:
```
aws rds create-db-instance ^
--database-insights-mode advanced ^
--engine postgresql ^
--db-instance-identifier sample-db-identifier ^
--enable-performance-insights ^
--performance-insights-retention-period 465
```
------
#### [ RDS API ]
To turn on the Advanced mode of Database Insights when you create a DB instance or Multi-AZ DB cluster, specify the following parameters for your [CreateDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBInstance.html) or [CreateDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBCluster.html) Amazon RDS API operation.
+ `DatabaseInsightsMode` to `advanced`
+ `EnablePerformanceInsights` to `True`
+ `PerformanceInsightsRetentionPeriod` to at least 465 days
------
## Turning on the Advanced mode of Database Insights when modifying a DB instance or Multi-AZ DB cluster
Turn on Database Insights when modifying a database for Amazon RDS. Modifying a DB instance to enable the Advanced mode of Database Insights doesn't cause downtime.
**Note**
To enable Database Insights, each DB instance in a Multi-AZ DB cluster must have the same Performance Insights and Enhanced Monitoring settings.
------
#### [ Console ]
In the console, you can turn on the Advanced mode of Database Insights when you modify a DB instance or Multi-AZ DB cluster.
**To turn on the Advanced mode of Database Insights when modifying a DB instance or Multi-AZDB cluster using the console**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Databases**.
1. Choose a DB instance or Multi-AZ DB cluster, and choose **Modify**.
1. In the **Database Insights** section, select **Advanced mode**. Then, choose the following options:
+ **Retention** – The amount of time to retain Performance Insights data. The retention period must be 15 months for the Advanced mode of Database Insights.
+ **AWS KMS key** – Specify your KMS key. Performance Insights encrypts all potentially sensitive data using your KMS key. Data is encrypted in flight and at rest. For more information, see [Encrypting Amazon RDS resources](Overview.Encryption.md).
1. Choose **Continue**.
1. For **Scheduling of Modifications**, choose **Apply immediately**. If you choose **Apply during the next scheduled maintenance window**, your database ignores this setting and turns on the Advanced mode of Database Insights immediately.
1. Choose **Modify instance**.
------
#### [ AWS CLI ]
To turn on the Advanced mode of Database Insights when modifying a DB instance or Multi-AZ DB cluster, call the [modify-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-instance.html) or [modify-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-cluster.html) AWS CLI command and supply the following values:
+ `--database-insights-mode advanced` to turn on the Advanced mode of Database Insights.
+ `--db-instance-identifier` – The identifier for the DB instance or `--db-cluster-identifier` – The identifier for the Multi-AZ DB cluster.
+ `--enable-performance-insights` to turn on Performance Insights for Database Insights.
+ `--performance-insights-retention-period` – The retention period for data for your DB instance. To turn on the Advanced mode of Database Insights, the retention period must be at least 465 days.
The following example enables the Advanced mode of Database Insights when modifying a DB instance.
For Linux, macOS, or Unix:
```
aws rds modify-db-instance \
--database-insights-mode advanced \
--db-instance-identifier sample-db-identifier \
--enable-performance-insights \
--performance-insights-retention-period 465
```
For Windows:
```
aws rds modify-db-instance ^
--database-insights-mode advanced ^
--db-instance-identifier sample-db-identifier ^
--enable-performance-insights ^
--performance-insights-retention-period 465
```
------
#### [ RDS API ]
To turn on the Advanced mode of Database Insights when you modify a DB instance or Multi-AZ DB cluster, specify the following parameters for your [ModifyDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBInstance.html) or [ModifyDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBCluster.html) Amazon RDS API operation.
+ `DatabaseInsightsMode` to `advanced`
+ `EnablePerformanceInsights` to `True`
+ `PerformanceInsightsRetentionPeriod` to at least 465 days
------
# Turning on the Standard mode of Database Insights for Amazon RDS
To turn on the Standard mode of Database Insights for Amazon RDS, use the following procedures.
## Turning on the Standard mode of Database Insights when creating a DB instance or Multi-AZ DB cluster
Turn on the Standard mode of Database Insights when creating a database for Amazon RDS.
------
#### [ Console ]
In the console, you can turn on the Standard mode of Database Insights when you create a DB instance or Multi-AZ DB cluster.
**To turn on the Standard mode of Database Insights when creating a DB instance or Multi-AZDB cluster using the console**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Databases**.
1. Choose **Create database**.
1. In the **Database Insights** section, select **Standard mode**. Then, choose from the following options to turn Performance Insights on or off:
+ To turn off Performance Insights, deselect **Enable Performance Insights**.
+ To turn on Performance Insights, select **Enable Performance Insights**. To configure Performance Insights, specify the following options:
+ **Retention** – The amount of time to retain Performance Insights data. The retention period must be at least 7 days.
+ **AWS KMS key** – Specify your KMS key. Performance Insights encrypts all potentially sensitive data using your KMS key. Data is encrypted in flight and at rest. For more information, see [Encrypting Amazon RDS resources](Overview.Encryption.md).
1. Choose **Create database**.
------
#### [ AWS CLI ]
To turn on the Standard mode of Database Insights when creating a DB instance or Multi-AZ DB cluster, call the [create-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-instance.html) or [create-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-cluster.html) AWS CLI command and supply the following values:
+ `--database-insights-mode standard` to turn on the Standard mode of Database Insights.
+ `--engine` – The database engine for the DB instance.
+ `--db-instance-identifier` – The identifier for the DB instance or `--db-cluster-identifier` – The identifier for the Multi-AZ DB cluster.
+ `--enable-performance-insights` or `--no-enable-performance-insights` to turn Performance Insights on or off. If you specify `--enable-performance-insights`, you must also specify the `--performance-insights-retention-period` – The retention period for data for your DB instance. The retention period must be at least 7 days.
The following example enables the Standard mode of Database Insights and Performance Insights when creating a DB instance.
For Linux, macOS, or Unix:
```
aws rds create-db-instance \
--database-insights-mode standard \
--engine postgresql \
--db-instance-identifier sample-db-identifier \
--enable-performance-insights \
--performance-insights-retention-period 7
```
For Windows:
```
aws rds create-db-instance ^
--database-insights-mode standard ^
--engine postgresql ^
--db-instance-identifier sample-db-identifier ^
--enable-performance-insights ^
--performance-insights-retention-period 7
```
The following example enables the Standard mode of Database Insights and disables Performance Insights when creating a DB instance.
For Linux, macOS, or Unix:
```
aws rds create-db-instance \
--database-insights-mode standard \
--engine postgresql \
--db-instance-identifier sample-db-identifier \
--no-enable-performance-insights
```
For Windows:
```
aws rds create-db-instance ^
--database-insights-mode standard ^
--engine postgresql ^
--db-instance-identifier sample-db-identifier ^
--no-enable-performance-insights
```
------
#### [ RDS API ]
To turn on the Standard mode of Database Insights when you create a DB instance or Multi-AZ DB cluster, specify the following parameters for your [CreateDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBInstance.html) or [CreateDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBCluster.html) Amazon RDS API operation.
+ `DatabaseInsightsMode` to `standard`
+ `EnablePerformanceInsights` to `True` or `False`. If you set `EnablePerformanceInsights` to `True`, you must set `PerformanceInsightsRetentionPeriod` to at least 7 days.
------
## Turning on the Standard mode of Database Insights when modifying a DB instance or Multi-AZ DB cluster
Turn on Standard mode of Database Insights when modifying a database for Amazon RDS. Modifying a DB instance to enable the Standard mode of Database Insights doesn't cause downtime.
**Note**
To enable Database Insights, each DB instance in a Multi-AZ DB cluster must have the same Performance Insights and Enhanced Monitoring settings.
------
#### [ Console ]
In the console, you can turn on the Standard mode of Database Insights when you modify a DB instance or Multi-AZ DB cluster.
**To turn on the Standard mode of Database Insights when modifying a DB instance or Multi-AZDB cluster using the console**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Databases**.
1. Choose a DB instance or Multi-AZ DB cluster, and choose **Modify**.
1. In the **Database Insights** section, select **Standard mode**. Then, choose from the following options:
+ To turn off Performance Insights, deselect **Enable Performance Insights**.
+ To turn on Performance Insights, select **Enable Performance Insights**. To configure Performance Insights, specify the following options:
+ **Retention** – The amount of time to retain Performance Insights data. The retention period must be at least 7 days.
+ **AWS KMS key** – Specify your KMS key. Performance Insights encrypts all potentially sensitive data using your KMS key. Data is encrypted in flight and at rest. For more information, see [Encrypting Amazon RDS resources](Overview.Encryption.md).
1. Choose **Continue**.
1. For **Scheduling of Modifications**, choose **Apply immediately**. If you choose **Apply during the next scheduled maintenance window**, your database ignores this setting and turns on the Standard mode of Database Insights immediately.
1. Choose **Modify instance**.
------
#### [ AWS CLI ]
To turn on the Standard mode of Database Insights when modifying a DB instance or Multi-AZ DB cluster, call the [modify-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-instance.html) or [modify-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-cluster.html) AWS CLI command and supply the following values:
+ `--database-insights-mode standard` to turn on the Standard mode of Database Insights.
+ `--db-instance-identifier` – The identifier for the DB instance or `--db-cluster-identifier` – The identifier for the Multi-AZ DB cluster.
+ `--enable-performance-insights` or `--no-enable-performance-insights` to turn Performance Insights on or off. If you specify `--enable-performance-insights`, you must also specify the `--performance-insights-retention-period` – The retention period for data for your DB instance or Multi-AZ DB cluster. The retention period must be at least 7 days.
The following example enables the Standard mode of Database Insights and enables Performance Insights when modifying a DB instance.
For Linux, macOS, or Unix:
```
aws rds modify-db-instance \
--database-insights-mode standard \
--db-instance-identifier sample-db-identifier \
--enable-performance-insights \
--performance-insights-retention-period 7
```
For Windows:
```
aws rds modify-db-instance ^
--database-insights-mode standard ^
--db-instance-identifier sample-db-identifier ^
--enable-performance-insights ^
--performance-insights-retention-period 7
```
The following example enables the Standard mode of Database Insights and disables Performance Insights when modifying a DB instance.
For Linux, macOS, or Unix:
```
aws rds modify-db-instance \
--database-insights-mode standard \
--db-instance-identifier sample-db-identifier \
--no-enable-performance-insights
```
For Windows:
```
aws rds modify-db-instance ^
--database-insights-mode standard ^
--db-instance-identifier sample-db-identifier ^
--no-enable-performance-insights
```
------
#### [ RDS API ]
To turn on the Standard mode of Database Insights when you modify a DB instance or Multi-AZ DB cluster, specify the following parameters for your [ModifyDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBInstance.html) or [ModifyDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBCluster.html) Amazon RDS API operation.
+ `DatabaseInsightsMode` to `standard`
+ `EnablePerformanceInsights` to `True` or `False`. If you set `EnablePerformanceInsights` to `True`, you must set `PerformanceInsightsRetentionPeriod` to at least 7 days.
------
# Configuring your database to monitor slow SQL queries with Database Insights for Amazon RDS
To monitor slow SQL queries for your database, you can use the **Slow SQL Queries** section in the Database Insights dashboard. Before configuring your database to monitor slow SQL queries, the **Slow SQL Queries** section is blank.
For more information about monitoring slow SQL queries in the Database Insights dashboard, see [Viewing the Database Instance Dashboard for CloudWatch Database Insights](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/Database-Insights-Database-Instance-Dashboard.html) in the *Amazon CloudWatch User Guide*.
To configure your database to monitor slow SQL queries with Database Insights, complete the following steps:
1. Enable log exports to CloudWatch Logs.
1. Create or modify the DB parameter group for your DB instance.
For information about configuring log exports, see [Publishing database logs to Amazon CloudWatch Logs](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_LogAccess.html#USER_LogAccess.Procedural.UploadtoCloudWatch) in the *Amazon RDS User Guide*.
To create or modify your DB parameter group, see the following topics.
+ [Creating a DB parameter group in Amazon RDS](USER_WorkingWithParamGroups.Creating.md)
+ [Modifying parameters in a DB parameter group in Amazon RDS](USER_WorkingWithParamGroups.Modifying.md)
------
#### [ RDS for MariaDB ]
To configure your RDS for MariaDB DB instance to monitor slow SQL queries, you can use the following parameter combination as an example:
+ `log_slow_query` – set to `1`
+ `log_slow_query_time` – set to `1.0`
+ `log_output` – set to `FILE`
This is one possible configuration. For a comprehensive guide to MariaDB slow query log parameters and additional configuration options, see the [MariaDB documentation for the slow query log](https://mariadb.com/kb/en/slow-query-log-overview/).
------
#### [ RDS for MySQL ]
To configure your RDS for MySQL DB instance to monitor slow SQL queries, you can use the following parameter combination as an example:
+ `slow_query_log` – set to `1`
+ `long_query_time` – set to `1.0`
+ `log_output` – set to `FILE`
This is one possible configuration. For a comprehensive guide to MySQL slow query log parameters and additional configuration options, see the [MySQL documentation for the slow query log](https://dev.mysql.com/doc/refman/8.0/en/slow-query-log.html).
------
#### [ RDS for PostgreSQL ]
To configure your RDS for PostgreSQL DB instance to monitor slow SQL queries, you can use the following parameter combination as an example. Note that setting these parameters might reduce the performance of your DB instance.
+ `log_min_duration_statement` – set to `1000`
+ `log_statement` – set to `none`
+ `log_destination` – set to `stderr`
This is one possible configuration. For a comprehensive guide to PostgreSQL logging parameters and additional configuration options, see the [PostgreSQL documentation for logging configuration](https://www.postgresql.org/docs/current/runtime-config-logging.html).
------
**Note**
For RDS for MySQL, you can configure the parameter `long_query_time` with 1‐microsecond granularity. For example, you can set this parameter to `0.000001`. Depending on the amount of queries on the DB instance, the value of the parameter `long_query_time` can reduce performance. Start with the value `1.0`, and adjust it based on your workload. When you set this parameter to `0`, Database Insights logs all queries.
For information about RDS for MariaDB, RDS for MySQL, and RDS for PostgreSQL logs, see the following.
+ [MariaDB database log files](USER_LogAccess.Concepts.MariaDB.md)
+ [MySQL database log files](USER_LogAccess.Concepts.MySQL.md)
+ [ RDS for PostgreSQL database log files](USER_LogAccess.Concepts.PostgreSQL.md)
# Considerations for Database Insights for Amazon RDS
Following are considerations for Database Insights for Amazon RDS.
+ You can't manage Database Insights for a DB instance in a Multi-AZ DB cluster.
+ To enable the Advanced mode of Database Insights, you must enable Performance Insights and set the Performance Insights retention period to at least 465 days (15 months). There is no additional cost to set the Performance Insights retention period to 15 months besides the cost of Database Insights. For information about pricing for Database Insights, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
+ To enable Database Insights, each DB instance in a Multi-AZ DB cluster must have the same Performance Insights and Enhanced Monitoring settings.
+ Modifying a DB instance to enable either mode of Database Insights doesn't cause downtime.
# Monitoring DB load with Performance Insights on Amazon RDS
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
Performance Insights expands on existing Amazon RDS monitoring features to illustrate and help you analyze your database performance. With the Performance Insights dashboard, you can visualize the database load on your Amazon RDS DB instance load and filter the load by waits, SQL statements, hosts, or users. For information about using Performance Insights with Amazon DocumentDB, see *[Amazon DocumentDB Developer Guide](https://docs.aws.amazon.com/documentdb/latest/developerguide/performance-insights.html)*.
**Topics**
+ [
# Overview of Performance Insights on Amazon RDS
](USER_PerfInsights.Overview.md)
+ [
# Turning Performance Insights on and off for Amazon RDS
](USER_PerfInsights.Enabling.md)
+ [
# Overview of the Performance Schema for Performance Insights on Amazon RDS for MariaDB or MySQL
](USER_PerfInsights.EnableMySQL.md)
+ [
# Configuring access policies for Performance Insights
](USER_PerfInsights.access-control.md)
+ [
# Analyzing metrics with the Performance Insights dashboard
](USER_PerfInsights.UsingDashboard.md)
+ [
# Viewing Performance Insights proactive recommendations
](USER_PerfInsights.InsightsRecommendationViewDetails.md)
+ [
# Retrieving metrics with the Performance Insights API for Amazon RDS
](USER_PerfInsights.API.md)
+ [
# Logging Performance Insights calls using AWS CloudTrail
](USER_PerfInsights.CloudTrail.md)
+ [
# Performance Insights API and interface VPC endpoints (AWS PrivateLink)
](pi-vpc-interface-endpoints.md)
# Overview of Performance Insights on Amazon RDS
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
By default, RDS enables Performance Insights in the console create wizard for all Amazon RDS engines. If you have more than one database on a DB instance, Performance Insights aggregates performance data.
You can find an overview of Performance Insights for Amazon RDS in the following video.
[](http://www.youtube.com/watch?v=yOeWcPBT458)
**Important**
The following topics describe using Amazon RDS Performance Insights with non-Aurora DB engines. For information about using Amazon RDS Performance Insights with Amazon Aurora, see [Using Amazon RDS Performance Insights](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/USER_PerfInsights.html) in the *Amazon Aurora User Guide*.
**Topics**
+ [
# Database load
](USER_PerfInsights.Overview.ActiveSessions.md)
+ [
# Maximum CPU
](USER_PerfInsights.Overview.MaxCPU.md)
+ [
# Amazon RDS DB engine, Region, and instance class support for Performance Insights
](USER_PerfInsights.Overview.Engines.md)
+ [
# Pricing and data retention for Performance Insights
](USER_PerfInsights.Overview.cost.md)
# Database load
*Database load (DB load)* measures the level of session activity in your database. `DBLoad` is the key metric in Performance Insights, and Performance Insights collects DB load every second.
**Topics**
+ [
## Active sessions
](#USER_PerfInsights.Overview.ActiveSessions.active-sessions)
+ [
## Average active sessions
](#USER_PerfInsights.Overview.ActiveSessions.AAS)
+ [
## Average active executions
](#USER_PerfInsights.Overview.ActiveSessions.AAE)
+ [
## Dimensions
](#USER_PerfInsights.Overview.ActiveSessions.dimensions)
## Active sessions
A *database session* represents an application's dialogue with a relational database. An active session is a connection that has submitted work to the DB engine and is waiting for a response.
A session is active when it's either running on CPU or waiting for a resource to become available so that it can proceed. For example, an active session might wait for a page (or block) to be read into memory, and then consume CPU while it reads data from the page.
## Average active sessions
The *average active sessions (AAS)* is the unit for the `DBLoad` metric in Performance Insights. It measures how many sessions are concurrently active on the database.
Every second, Performance Insights samples the number of sessions concurrently running a query. For each active session, Performance Insights collects the following data:
+ SQL statement
+ Session state (running on CPU or waiting)
+ Host
+ User running the SQL
Performance Insights calculates the AAS by dividing the total number of sessions by the number of samples for a specific time period. For example, the following table shows 5 consecutive samples of a running query taken at 1-second intervals.
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.ActiveSessions.html)
In the preceding example, the DB load for the time interval was 2 AAS. This measurement means that, on average, 2 sessions were active at any given time during the interval when the 5 samples were taken.
## Average active executions
The average active executions (AAE) per second is related to AAS. To calculate the AAE, Performance Insights divides the total execution time of a query by the time interval. The following table shows the AAE calculation for the same query in the preceding table.
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.ActiveSessions.html)
In most cases, the AAS and AAE for a query are approximately the same. However, because the inputs to the calculations are different data sources, the calculations often vary slightly.
## Dimensions
The `db.load` metric is different from the other time-series metrics because you can break it into subcomponents called dimensions. You can think of dimensions as "slice by" categories for the different characteristics of the `DBLoad` metric.
When you are diagnosing performance issues, the following dimensions are often the most useful:
**Topics**
+ [
### Wait events
](#USER_PerfInsights.Overview.ActiveSessions.waits)
+ [
### Top SQL
](#USER_PerfInsights.Overview.ActiveSessions.top-sql)
+ [
### Plans
](#USER_PerfInsights.Overview.ActiveSessions.plans)
For a complete list of dimensions for the Amazon RDS engines, see [DB load sliced by dimensions](USER_PerfInsights.UsingDashboard.Components.md#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.dims).
### Wait events
A *wait event* causes a SQL statement to wait for a specific event to happen before it can continue running. Wait events are an important dimension, or category, for DB load because they indicate where work is impeded.
Every active session is either running on the CPU or waiting. For example, sessions consume CPU when they search memory for a buffer, perform a calculation, or run procedural code. When sessions aren't consuming CPU, they might be waiting for a memory buffer to become free, a data file to be read, or a log to be written to. The more time that a session waits for resources, the less time it runs on the CPU.
When you tune a database, you often try to find out the resources that sessions are waiting for. For example, two or three wait events might account for 90 percent of DB load. This measure means that, on average, active sessions are spending most of their time waiting for a small number of resources. If you can find out the cause of these waits, you can attempt a solution.
Wait events vary by DB engine:
+ For information about all MariaDB and MySQL wait events, see [Wait Event Summary Tables](https://dev.mysql.com/doc/refman/8.0/en/performance-schema-wait-summary-tables.html) in the MySQL documentation.
+ For information about all PostgreSQL wait events, see [The Statistics Collector > Wait Event tables](https://www.postgresql.org/docs/current/monitoring-stats.html#WAIT-EVENT-TABLE) in the PostgreSQL documentation.
+ For information about all Oracle wait events, see [ Descriptions of Wait Events](https://docs.oracle.com/database/121/REFRN/GUID-2FDDFAA4-24D0-4B80-A157-A907AF5C68E2.htm#REFRN-GUID-2FDDFAA4-24D0-4B80-A157-A907AF5C68E2) in the Oracle documentation.
+ For information about all SQL Server wait events, see [ Types of Waits](https://docs.microsoft.com/en-us/sql/relational-databases/system-dynamic-management-views/sys-dm-os-wait-stats-transact-sql?view=sql-server-2017#WaitTypes) in the SQL Server documentation.
**Note**
For Oracle, background processes sometimes do work without an associated SQL statement. In these cases, Performance Insights reports the type of background process concatenated with a colon and the wait class associated with that background process. Types of background process include `LGWR`, `ARC0`, `PMON`, and so on.
For example, when the archiver is performing I/O, the Performance Insights report for it is similar to `ARC1:System I/O`. Occasionally, the background process type is also missing, and Performance Insights only reports the wait class, for example `:System I/O`.
### Top SQL
Where wait events show bottlenecks, top SQL shows which queries are contributing the most to DB load. For example, many queries might be currently running on the database, but a single query might consume 99 percent of the DB load. In this case, the high load might indicate a problem with the query.
By default, the Performance Insights console displays top SQL queries that are contributing to the database load. The console also shows relevant statistics for each statement. To diagnose performance problems for a specific statement, you can examine its execution plan.
### Plans
An *execution plan*, also called simply a *plan*, is a sequence of steps that access data. For example, a plan for joining tables `t1` and `t2` might loop through all rows in `t1` and compare each row to a row in `t2`. In a relational database, an *optimizer* is built-in code that determines the most efficient plan for a SQL query.
For DB instances, Performance Insights collects execution plans automatically. To diagnose SQL performance problems, examine the captured plans for high-resource SQL queries. The plans show how the database has parsed and run queries.
To learn how to analyze DB load using plans, see:
+ Oracle: [Analyzing Oracle execution plans using the Performance Insights dashboard for Amazon RDS](USER_PerfInsights.UsingDashboard.AccessPlans.md)
+ SQL Server: [Analyzing SQL Server execution plans using the Performance Insights dashboard for Amazon RDS](USER_PerfInsights.UsingDashboard.AccessPlansSqlServer.md)
#### Plan capture
Every five minutes, Performance Insights identifies the most resource-intensive queries and captures their plans. Thus, you don't need to manually collect and manage a huge number of plans. Instead, you can use the **Top SQL** tab to focus on the plans for the most problematic queries.
**Note**
Performance Insights doesn't capture plans for queries whose text exceeds the maximum collectable query text limit. For more information, see [Accessing more SQL text in the Performance Insights dashboard](USER_PerfInsights.UsingDashboard.SQLTextSize.md).
The retention period for execution plans is the same as for your Performance Insights data. The retention setting is **Default (7 days)**. To retain your performance data for longer, specify 1–24 months. For more information about retention periods, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
#### Digest queries
The **Top SQL** tab shows digest queries by default. A digest query doesn't itself have a plan, but all queries that use literal values have plans. For example, a digest query might include the text `WHERE `email`=?`. The digest might contain two queries, one with the text `WHERE email=user1@example.com` and another with `WHERE email=user2@example.com`. Each of these literal queries might include multiple plans.
When you select a digest query, the console shows all plans for child statements of the selected digest. Thus, you don't need to look through all the child statements to find the plan. You might see plans that aren’t in the displayed list of top 10 child statements. The console shows plans for all child queries for which plans have been collected, regardless of whether the queries are in the top 10.
# Maximum CPU
In the dashboard, the **Database load** chart collects, aggregates, and displays session information. To see whether active sessions are exceeding the maximum CPU, look at their relationship to the **Max vCPU** line. Performance Insights determines the **Max vCPU** value by the number of vCPU (virtual CPU) cores for your DB instance.
One process can run on a vCPU at a time. If the number of processes exceeds the number of vCPUs, the processes start queuing. When queuing increases, database performance decreases. If the DB load is often above the **Max vCPU** line, and the primary wait state is CPU, the CPU is overloaded. In this case, you might want to throttle connections to the instance, tune any SQL queries with a high CPU load, or consider a larger instance class. High and consistent instances of any wait state indicate that there might be bottlenecks or resource contention issues to resolve. This can be true even if the DB load doesn't cross the **Max vCPU** line.
# Amazon RDS DB engine, Region, and instance class support for Performance Insights
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
The following table provides Amazon RDS DB engines that support Performance Insights.
**Note**
For Amazon Aurora, see [Amazon Aurora DB engine support for Performance Insights](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/USER_PerfInsights.Overview.Engines.html) in *Amazon Aurora User Guide*.
| Amazon RDS DB engine | Supported engine versions and Regions | Instance class restrictions |
| --- | --- | --- |
| Amazon RDS for MariaDB | For more information on version and Region availability of Performance Insights with RDS for MariaDB, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | Performance Insights isn't supported for the following instance classes: [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.Engines.html) |
| RDS for MySQL | For more information on version and Region availability of Performance Insights with RDS for MySQL, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | Performance Insights isn't supported for the following instance classes: [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.Engines.html) |
| Amazon RDS for Microsoft SQL Server | For more information on version and Region availability of Performance Insights with RDS for SQL Server, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | N/A |
| Amazon RDS for PostgreSQL | For more information on version and Region availability of Performance Insights with RDS for PostgreSQL, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | N/A |
| Amazon RDS for Oracle | For more information on version and Region availability of Performance Insights with RDS for Oracle, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md). | N/A |
## Amazon RDS DB engine, Region, and instance class support for Performance Insights features
The following table provides Amazon RDS DB engines that support Performance Insights features.
| Feature | [Pricing tier](https://aws.amazon.com/rds/performance-insights/pricing/) | [Supported regions](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.RegionsAndAvailabilityZones.html#Concepts.RegionsAndAvailabilityZones.Regions) | [ Supported DB engines](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Welcome.html#Welcome.Concepts.DBInstance) | [Supported instance classes](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Concepts.DBInstanceClass.html#Concepts.DBInstanceClass.Types) |
| --- | --- | --- | --- | --- |
| [SQL statistics for Performance Insights](sql-statistics.md) | All | All | All | All |
| [Analyzing Oracle execution plans using the Performance Insights dashboard for Amazon RDS](USER_PerfInsights.UsingDashboard.AccessPlans.md) | All | All | RDS for Oracle | All |
| [Analyzing database performance for a period of time](USER_PerfInsights.UsingDashboard.AnalyzePerformanceTimePeriod.md) | Paid tier only | All | RDS for PostgreSQL | All |
| [Viewing Performance Insights proactive recommendations](USER_PerfInsights.InsightsRecommendationViewDetails.md) | Paid tier only | [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.Overview.Engines.html) | All | All |
# Pricing and data retention for Performance Insights
By default, Performance Insights includes 7 days of performance data history and 1 million API requests per month. You can also purchase longer retention periods. For complete pricing information, see [Performance Insights Pricing](https://aws.amazon.com/rds/performance-insights/pricing/).
In the RDS console, you can choose any of the following retention periods for your Performance Insights data:
+ **Default (7 days)**
+ ***n* months**, where ***n*** is a number from 1–24
![\[Choose a retention period for your Performance Insights data.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-retention-periods.png)
To learn how to set a retention period using the AWS CLI, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md).
**Note**
Stopping a DB instance or Multi-AZ DB cluster with Performance Insights enabled doesn't affect data retention. While a DB instance or Multi-AZ DB cluster is stopped, Performance Insights won't collect any data.
# Turning Performance Insights on and off for Amazon RDS
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
You can turn on Performance Insights for your DB instance or Multi-AZ DB cluster when you create it. If needed, you can turn it off later by modifying your DB instance from the console. Turning Performance Insights on and off doesn't cause downtime, a reboot, or a failover.
**Note**
Performance Schema is an optional performance tool used by Amazon RDS for MariaDB or MySQL. If you turn Performance Schema on or off, you need to reboot. If you turn Performance Insights on or off, however, you don't need to reboot. For more information, see [Overview of the Performance Schema for Performance Insights on Amazon RDS for MariaDB or MySQL](USER_PerfInsights.EnableMySQL.md).
The Performance Insights agent consumes limited CPU and memory on the DB host. When the DB load is high, the agent limits the performance impact by collecting data less frequently.
------
#### [ Console ]
In the console, you can turn Performance Insights on or off when you create or modify a DB instance or Multi-AZ DB cluster.
**Turning Performance Insights on or off when creating a DB instance or Multi-AZ DB cluster**
After creating a new DB instance or Multi-AZ DB cluster, Amazon RDS enables Performance Insights by default. To turn off Performance Insights, choose the option **Database Insights – Standard** and deselect the option **Enable Performance Insights**.
For more information, see the following topics.
+ To create a DB instance, follow the instructions for your DB engine in [Creating an Amazon RDS DB instance](USER_CreateDBInstance.md).
+ To create a Multi-AZ DB cluster, follow the instructions for your DB engine in [Creating a Multi-AZ DB cluster for Amazon RDS](create-multi-az-db-cluster.md).
The following screenshot shows the **Performance Insights** section.
![\[Turn on Performance Insights during DB instance or Multi-AZ DB cluster creation with console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_enabling.png)
If you choose **Enable Performance Insights**, you have the following options:
+ **Retention** (for the Standard mode of Database Insights only) – The amount of time to retain Performance Insights data. The retention setting is **Default (7 days)**. To retain your performance data for longer, specify 1–24 months. For more information about retention periods, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
+ **AWS KMS key** – Specify your AWS KMS key. Performance Insights encrypts all potentially sensitive data using your KMS key. Data is encrypted in flight and at rest. For more information, see [Changing an AWS KMS policy for Performance Insights](USER_PerfInsights.access-control.cmk-policy.md).
**Turning Performance Insights on or off when modifying a DB instance or Multi-AZ DB cluster**
In the console, you can modify a DB instance or Multi-AZ DB cluster to manage Performance Insights.
**To manage Performance Insights for a DB instance or Multi-AZ DB cluster using the console**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Databases**.
1. Choose a DB instance or Multi-AZ DB cluster, and choose **Modify**.
1. To turn on Performance Insights, select **Enable Performance Insights**. To turn off Performance Insights, choose the option **Database Insights – Standard** and deselect the option **Enable Performance Insights**.
If you choose **Enable Performance Insights**, you have the following options:
+ **Retention** (for the Standard mode of Database Insights only) – The amount of time to retain Performance Insights data. The retention setting is **Default (7 days)**. To retain your performance data for longer, specify 1–24 months. For more information about retention periods, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
+ **AWS KMS key** – Specify your KMS key. Performance Insights encrypts all potentially sensitive data using your KMS key. Data is encrypted in flight and at rest. For more information, see [Encrypting Amazon RDS resources](Overview.Encryption.md).
1. Choose **Continue**.
1. For **Scheduling of Modifications**, choose Apply immediately. If you choose Apply during the next scheduled maintenance window, your instance ignores this setting and turns on Performance Insights immediately.
1. Choose **Modify instance**.
------
#### [ AWS CLI ]
When you use the [create-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-instance.html) AWS CLI command, turn on Performance Insights by specifying `--enable-performance-insights` and set `--database-insights-mode` to either `advanced` or `standard`. To turn off Performance Insights, specify `--no-enable-performance-insights` and set `database-insights-mode` to `standard`.
You can also specify these values using the following AWS CLI commands:
+ [create-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-cluster.html)
+ [modify-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-cluster.html)
+ [create-db-instance-read-replica](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-instance-read-replica.html)
+ [modify-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-instance.html)
+ [restore-db-instance-from-s3](https://docs.aws.amazon.com/cli/latest/reference/rds/restore-db-instance-from-s3.html)
When you turn on Performance Insights in the CLI, you can optionally specify the number of days to retain Performance Insights data with the `--performance-insights-retention-period` option. You can specify `7`, *month* \$1 31 (where *month* is a number from 1–23), or `731`. For example, if you want to retain your performance data for 3 months, specify `93`, which is 3 \$1 31. The default is `7` days. For more information about retention periods, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
The following example turns on Performance Insights for `sample-db-cluster` and specifies that Performance Insights data is retained for 93 days (3 months).
For Linux, macOS, or Unix:
```
aws rds modify-db-cluster \
--database-insights-mode standard \
--db-cluster-identifier sample-db-instance \
--enable-performance-insights \
--performance-insights-retention-period 93
```
For Windows:
```
aws rds modify-db-cluster ^
--database-insights-mode standard ^
--db-cluster-identifier sample-db-instance ^
--enable-performance-insights ^
--performance-insights-retention-period 93
```
If you specify a retention period such as 94 days, which isn't a valid value, RDS issues an error.
```
An error occurred (InvalidParameterValue) when calling the CreateDBInstance operation:
Invalid Performance Insights retention period. Valid values are: [7, 31, 62, 93, 124, 155, 186, 217,
248, 279, 310, 341, 372, 403, 434, 465, 496, 527, 558, 589, 620, 651, 682, 713, 731]
```
**Note**
You can only toggle Performance Insights for an instance in a DB cluster where Performance Insights is not managed at the cluster level.
------
#### [ RDS API ]
When you create a new DB instance using the [CreateDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBInstance.html) operation Amazon RDS API operation, turn on Performance Insights by setting `EnablePerformanceInsights` to `True`. To turn off Performance Insights, set `EnablePerformanceInsights` to `False` and set `DatabaseInsightsMode` to `standard`.
You can also specify the `EnablePerformanceInsights` value using the following API operations:
+ [CreateDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBCluster.html) (Multi-AZ DB cluster)
+ [ModifyDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBCluster.html) (Multi-AZ DB cluster)
+ [ModifyDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBInstance.html)
+ [CreateDBInstanceReadReplica](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBInstanceReadReplica.html)
+ [RestoreDBInstanceFromS3](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_RestoreDBInstanceFromS3.html)
When you turn on Performance Insights, you can optionally specify the amount of time, in days, to retain Performance Insights data with the `PerformanceInsightsRetentionPeriod` parameter. You can specify `7`, *month* \$1 31 (where *month* is a number from 1–23), or `731`. For example, if you want to retain your performance data for 3 months, specify `93`, which is 3 \$1 31. The default is `7` days. For more information about retention periods, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
------
# Overview of the Performance Schema for Performance Insights on Amazon RDS for MariaDB or MySQL
The Performance Schema is an optional feature for monitoring Amazon RDS for MariaDB or MySQL runtime performance at a low level of detail. The Performance Schema is designed to have minimal impact on database performance. Performance Insights is a separate feature that you can use with or without the Performance Schema.
**Topics**
+ [
## Overview of the Performance Schema
](#USER_PerfInsights.EnableMySQL.overview)
+ [
## Performance Insights and the Performance Schema
](#USER_PerfInsights.effect-of-pfs)
+ [
## Automatic management of the Performance Schema by Performance Insights
](#USER_PerfInsights.EnableMySQL.options)
+ [
## Effect of a reboot on the Performance Schema
](#USER_PerfInsights.EnableMySQL.reboot)
+ [
# Determining whether Performance Insights is managing the Performance Schema
](USER_PerfInsights.EnableMySQL.determining-status.md)
+ [
# Turn on the Performance Schema for Amazon RDS for MariaDB or MySQL
](USER_PerfInsights.EnableMySQL.RDS.md)
## Overview of the Performance Schema
The Performance Schema monitors events in MariaDB and MySQL databases. An *event* is a database server action that consumes time and has been instrumented so that timing information can be collected. Examples of events include the following:
+ Function calls
+ Waits for the operating system
+ Stages of SQL execution
+ Groups of SQL statements
The `PERFORMANCE_SCHEMA` storage engine is a mechanism for implementing the Performance Schema feature. This engine collects event data using instrumentation in the database source code. The engine stores events in memory-only tables in the `performance_schema` database. You can query `performance_schema` just as you can query any other tables. For more information, see [MySQL Performance Schema](https://dev.mysql.com/doc/refman/8.0/en/performance-schema.html) in the *MySQL Reference Manual*.
## Performance Insights and the Performance Schema
Performance Insights and the Performance Schema are separate features, but they are connected. The behavior of Performance Insights for Amazon RDS for MariaDB or MySQL depends on whether the Performance Schema is turned on, and if so, whether Performance Insights manages the Performance Schema automatically. The following table describes the behavior.
| Performance Schema turned on | Performance Insights management mode | Performance Insights behavior |
| --- | --- | --- |
| Yes | Automatic | [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.EnableMySQL.html) |
| Yes | Manual | [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.EnableMySQL.html) |
| No | N/A | [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.EnableMySQL.html) |
## Automatic management of the Performance Schema by Performance Insights
When you create an Amazon RDS for MariaDB or MySQL DB instance with Performance Insights turned on, the Performance Schema is also turned on. In this case, Performance Insights automatically manages your Performance Schema parameters. This is the recommended configuration.
When Performance Insights manages the Performance Schema automatically, the **Source** of `performance_schema` is `System default`.
**Note**
Automatic management of the Performance Schema isn't supported for the t4g.medium instance class.
If you change the `performance_schema` parameter value manually, and then later want to change to automatic management, see [Turn on the Performance Schema for Amazon RDS for MariaDB or MySQL](USER_PerfInsights.EnableMySQL.RDS.md).
**Important**
When Performance Insights turns on the Performance Schema, it doesn't change the parameter group values. However, the values are changed on the DB instances that are running. The only way to see the changed values is to run the `SHOW GLOBAL VARIABLES` command.
## Effect of a reboot on the Performance Schema
Performance Insights and the Performance Schema differ in their requirements for DB instance reboots:
**Performance Schema**
To turn this feature on or off, you must reboot the DB instance.
**Performance Insights**
To turn this feature on or off, you don't need to reboot the DB instance.
If the Performance Schema isn't currently turned on, and you turn on Performance Insights without rebooting the DB instance, the Performance Schema won't be turned on.
# Determining whether Performance Insights is managing the Performance Schema
To find out whether Performance Insights is currently managing the Performance Schema for all supported major engine versions, review the following table.
| Setting of performance\$1schema parameter | Setting of the Source column | Performance Insights is managing the Performance Schema? |
| --- | --- | --- |
| 0 | System default | Yes |
| 0 or 1 | Modified | No |
In the following procedure, you determine whether Performance Insights is managing the Performance Schema automatically.
**To determine whether Performance Insights is managing the Performance Schema automatically**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Parameter groups**.
1. Select the name of the parameter group for your DB instance.
1. Enter **performance\$1schema** in the search bar.
1. Check whether **Source** is the system default and **Value** is **0**. If so, Performance Insights is managing the Performance Schema automatically.
In the example shown here, Performance Insights isn't managing the Performance Schema automatically.
![\[Shows that the settings for the performance_schema parameter are modified.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_schema_user.png)
# Turn on the Performance Schema for Amazon RDS for MariaDB or MySQL
Assume that Performance Insights is turned on for your DB instance or Multi-AZ DB cluster but isn't currently managing the Performance Schema. If you want to allow Performance Insights to manage the Performance Schema automatically, complete the following steps.
**To configure the Performance Schema for automatic management**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Choose **Parameter groups**.
1. Select the name of the parameter group for your DB instance or Multi-AZ DB cluster.
1. Choose **Edit**.
1. Enter **performance\$1schema** in the search bar.
1. Select the `performance_schema` parameter.
1. Choose **Set to default value**.
1. Confirm by choosing **Set values to default**.
1. Choose **Save Changes**.
1. Reboot the DB instance or Multi-AZ DB cluster.
**Important**
Whenever you turn the Performance Schema on or off, make sure to reboot the DB instance or Multi-AZ DB cluster.
For more information about modifying instance parameters, see [Modifying parameters in a DB parameter group in Amazon RDS](USER_WorkingWithParamGroups.Modifying.md). For more information about the dashboard, see [Analyzing metrics with the Performance Insights dashboard](USER_PerfInsights.UsingDashboard.md). For more information about the MySQL performance schema, see [MySQL Performance Schema](https://dev.mysql.com/doc/refman/8.0/en/performance-schema.html) (for 8.0) and [MySQL Performance Schema](https://dev.mysql.com/doc/refman/8.4/en/performance-schema.html) (for 8.4) in the MySQL documentation.
# Configuring access policies for Performance Insights
To access Performance Insights, a principal must have the appropriate permissions from AWS Identity and Access Management (IAM).
**Note**
To use Performance Insights with a customer-managed key, grant users the `kms:Decrypt` and `kms:GenerateDataKey` permissions for your AWS AWS KMS key.
Access Performance Insights using these methods:
+ [Attach the `AmazonRDSPerformanceInsightsReadOnly` managed policy for read-only access](USER_PerfInsights.access-control.managed-policy.md)
+ [Attach the `AmazonRDSPerformanceInsightsFullAccess` managed policy for access to all operations of the Performance Insights API](USER_PerfInsights.access-control.FullAccess-managed-policy.md)
+ [Create a custom IAM policy with specific permissions](USER_PerfInsights.access-control.custom-policy.md)
+ [Configure AWS KMS permissions for encrypted Performance Insights data](USER_PerfInsights.access-control.cmk-policy.md)
+ [Set up fine-grained access using resource-level permissions](USER_PerfInsights.access-control.dimensionAccess-policy.md)
+ [Use tag-based access control to manage permissions through resource tags](USER_PerfInsights.access-control.tag-based-policy.md)
# Attaching the AmazonRDSPerformanceInsightsReadOnly policy to an IAM principal
`AmazonRDSPerformanceInsightsReadOnly` is an AWS managed policy that grants access to all read-only operations of the Amazon RDS Performance Insights API.
If you attach `AmazonRDSPerformanceInsightsReadOnly` to a permission set or role, you must also attach the following CloudWatch permissions:
+ `GetMetricStatistics`
+ `ListMetrics`
+ `GetMetricData`
With these permissions, the recipient can use Performance Insights with other console features.
For more information about CloudWatch permissions, see [Amazon CloudWatch permissions reference](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/permissions-reference-cw.html).
For more information about `AmazonRDSPerformanceInsightsReadOnly`, see [AWS managed policy: AmazonRDSPerformanceInsightsReadOnly](rds-security-iam-awsmanpol.md#rds-security-iam-awsmanpol-AmazonRDSPerformanceInsightsReadOnly).
# Attaching the AmazonRDSPerformanceInsightsFullAccess policy to an IAM principal
`AmazonRDSPerformanceInsightsFullAccess` is an AWS managed policy that grants access to all operations of the Amazon RDS Performance Insights API.
If you attach `AmazonRDSPerformanceInsightsFullAccess` to a permission set or role, you must also attach the following CloudWatch permissions:
+ `GetMetricStatistics`
+ `ListMetrics`
+ `GetMetricData`
With these permissions, the recipient can use Performance Insights with other console features.
For more information about CloudWatch permissions, see [Amazon CloudWatch permissions reference](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/permissions-reference-cw.html).
For more information about `AmazonRDSPerformanceInsightsFullAccess`, see [AWS managed policy: AmazonRDSPerformanceInsightsFullAccess](rds-security-iam-awsmanpol.md#rds-security-iam-awsmanpol-AmazonRDSPerformanceInsightsFullAccess).
# Creating a custom IAM policy for Performance Insights
For users who don't have either the `AmazonRDSPerformanceInsightsReadOnly` or `AmazonRDSPerformanceInsightsFullAccess` policy, you can grant access to Performance Insights by creating or modifying a user-managed IAM policy. When you attach the policy to an IAM permission set or role, the recipient can use Performance Insights.
**To create a custom policy**
1. Open the IAM console at [https://console.aws.amazon.com/iam/](https://console.aws.amazon.com/iam/).
1. In the navigation pane, choose **Policies**.
1. Choose **Create policy**.
1. On the **Create Policy** page, choose the **JSON** option.
1. Copy and paste the text provided in the *JSON policy document* section in the *AWS Managed Policy Reference Guide* for [https://docs.aws.amazon.com/aws-managed-policy/latest/reference/AmazonRDSPerformanceInsightsReadOnly.html](https://docs.aws.amazon.com/aws-managed-policy/latest/reference/AmazonRDSPerformanceInsightsReadOnly.html) or [https://docs.aws.amazon.com/aws-managed-policy/latest/reference/AmazonRDSPerformanceInsightsFullAccess.html](https://docs.aws.amazon.com/aws-managed-policy/latest/reference/AmazonRDSPerformanceInsightsFullAccess.html) policy.
1. Choose **Review policy**.
1. Provide a name for the policy and optionally a description, and then choose **Create policy**.
You can now attach the policy to a permission set or role. The following procedure assumes that you already have a user available for this purpose.
**To attach the policy to a user**
1. Open the IAM console at [https://console.aws.amazon.com/iam/](https://console.aws.amazon.com/iam/).
1. In the navigation pane, choose **Users**.
1. Choose an existing user from the list.
**Important**
To use Performance Insights, make sure that you have access to Amazon RDS in addition to the custom policy. For example, the `AmazonRDSPerformanceInsightsReadOnly` predefined policy provides read-only access to Amazon RDS. For more information, see [Managing access using policies](UsingWithRDS.IAM.md#security_iam_access-manage).
1. On the **Summary** page, choose **Add permissions**.
1. Choose **Attach existing policies directly**. For **Search**, type the first few characters of your policy name, as shown in the following image.
![\[Choose a Policy\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_attach_iam_policy.png)
1. Choose your policy, and then choose **Next: Review**.
1. Choose **Add permissions**.
# Changing an AWS KMS policy for Performance Insights
Performance Insights uses an AWS KMS key to encrypt sensitive data. When you enable Performance Insights through the API or the console, you can do either of the following:
+ Choose the default AWS managed key.
Amazon RDS uses the AWS managed key for your new DB instance. Amazon RDS creates an AWS managed key for your AWS account. Your AWS account has a different AWS managed key for Amazon RDS for each AWS Region.
+ Choose a customer managed key.
If you specify a customer managed key, users in your account that call the Performance Insights API need the `kms:Decrypt` and `kms:GenerateDataKey` permissions on the KMS key. You can configure these permissions through IAM policies. However, we recommend that you manage these permissions through your KMS key policy. For more information, see [Key policies in AWS KMS](https://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html) in the *AWS Key Management Service Developer Guide*.
**Example**
The following example shows how to add statements to your KMS key policy. These statements allow access to Performance Insights. Depending on how you use the KMS key, you might want to change some restrictions. Before adding statements to your policy, remove all comments.
****
```
{
"Version":"2012-10-17",
"Id" : "your-policy",
"Statement" : [
{
"Sid" : "AllowViewingRDSPerformanceInsights",
"Effect": "Allow",
"Principal": {
"AWS": [
"arn:aws:iam::444455556666:role/Role1"
]
},
"Action": [
"kms:Decrypt",
"kms:GenerateDataKey"
],
"Resource": "*",
"Condition" : {
"StringEquals" : {
"kms:ViaService" : "rds.us-east-1.amazonaws.com"
},
"ForAnyValue:StringEquals": {
"kms:EncryptionContext:aws:pi:service": "rds",
"kms:EncryptionContext:service": "pi",
"kms:EncryptionContext:aws:rds:db-id": "db-AAAAABBBBBCCCCDDDDDEEEEE"
}
}
}
]
}
```
## How Performance Insights uses AWS KMS customer managed key
Performance Insights uses customer managed keys to encrypt sensitive data. When you turn on Performance Insights, you can provide an AWS KMS key through the API. Performance Insights creates AWS KMS permissions on this key. It uses the key and performs the necessary operations to process sensitive data. Sensitive data includes fields such as user, database, application, and SQL query text. Performance Insights ensures that the data remains encrypted both at rest and in-flight.
## How Performance Insights IAM works with AWS KMS
IAM gives permissions to specific APIs. Performance Insights has the following public APIs, which you can restrict using IAM policies:
+ `DescribeDimensionKeys`
+ `GetDimensionKeyDetails`
+ `GetResourceMetadata`
+ `GetResourceMetrics`
+ `ListAvailableResourceDimensions`
+ `ListAvailableResourceMetrics`
You can use the following API requests to get sensitive data.
+ `DescribeDimensionKeys`
+ `GetDimensionKeyDetails`
+ `GetResourceMetrics`
When you use the API to get sensitive data, Performance Insights leverages the caller's credentials. This check ensures that access to sensitive data is limited to those with access to the KMS key.
When calling these APIs, you need permissions to call the API through the IAM policy and permissions to invoke the `kms:decrypt` action through the AWS KMS key policy.
The `GetResourceMetrics` API can return both sensitive and non-sensitive data. The request parameters determine whether the response should include sensitive data. The API returns sensitive data when the request includes a sensitive dimension in either the filter or group-by parameters.
For more information about the dimensions that you can use with the `GetResourceMetrics` API, see [DimensionGroup](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DimensionGroup.html).
**Examples**
The following example requests the sensitive data for the `db.user` group:
```
POST / HTTP/1.1
Host:
Accept-Encoding: identity
X-Amz-Target: PerformanceInsightsv20180227.GetResourceMetrics
Content-Type: application/x-amz-json-1.1
User-Agent:
X-Amz-Date:
Authorization: AWS4-HMAC-SHA256 Credential=, SignedHeaders=, Signature=
Content-Length:
{
"ServiceType": "RDS",
"Identifier": "db-ABC1DEFGHIJKL2MNOPQRSTUV3W",
"MetricQueries": [
{
"Metric": "db.load.avg",
"GroupBy": {
"Group": "db.user",
"Limit": 2
}
}
],
"StartTime": 1693872000,
"EndTime": 1694044800,
"PeriodInSeconds": 86400
}
```
**Example**
The following example requests the non-sensitive data for the `db.load.avg` metric:
```
POST / HTTP/1.1
Host:
Accept-Encoding: identity
X-Amz-Target: PerformanceInsightsv20180227.GetResourceMetrics
Content-Type: application/x-amz-json-1.1
User-Agent:
X-Amz-Date:
Authorization: AWS4-HMAC-SHA256 Credential=, SignedHeaders=, Signature=
Content-Length:
{
"ServiceType": "RDS",
"Identifier": "db-ABC1DEFGHIJKL2MNOPQRSTUV3W",
"MetricQueries": [
{
"Metric": "db.load.avg"
}
],
"StartTime": 1693872000,
"EndTime": 1694044800,
"PeriodInSeconds": 86400
}
```
# Granting fine-grained access for Performance Insights
Fine-grained access control offers additional ways of controlling access to Performance Insights. This access control can allow or deny access to individual dimensions for `GetResourceMetrics`, `DescribeDimensionKeys`, and `GetDimensionKeyDetails` Performance Insights actions. To use fine-grained access, specify dimensions in the IAM policy by using condition keys. The evaluation of the access follows the IAM policy evaluation logic. For more information, see [Policy evaluation logic](https://docs.aws.amazon.com/IAM/latest/UserGuide/reference_policies_evaluation-logic.html) in the *IAM User Guide*. If the IAM policy statement doesn't specify any dimension, then the statement controls access to all the dimensions for the specified action. For the list of available dimensions, see [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DimensionGroup.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DimensionGroup.html).
To find out the dimensions that your credentials are authorized to access, use the `AuthorizedActions` parameter in `ListAvailableResourceDimensions` and specify the action. The allowed values for `AuthorizedActions` are as follows:
+ `GetResourceMetrics`
+ `DescribeDimensionKeys`
+ `GetDimensionKeyDetails`
For example, if you specify `GetResourceMetrics` to the `AuthorizedActions` parameter, `ListAvailableResourceDimensions` returns the list of dimensions that the `GetResourceMetrics` action is authorized to access. If you specify multiple actions in the `AuthorizedActions` parameter, then `ListAvailableResourceDimensions` returns an intersection of dimensions that those actions are authorized to access.
**Example**
The following example provides access to the specified dimensions for `GetResourceMetrics` and `DescribeDimensionKeys` actions.
****
```
{
"Version":"2012-10-17",
"Statement": [
{
"Sid": "AllowToDiscoverDimensions",
"Effect": "Allow",
"Action": [
"pi:ListAvailableResourceDimensions"
],
"Resource": [
"arn:aws:pi:us-east-1:123456789012:metrics/rds/db-ABC1DEFGHIJKL2MNOPQRSTUV3W"
]
},
{
"Sid": "SingleAllow",
"Effect": "Allow",
"Action": [
"pi:GetResourceMetrics",
"pi:DescribeDimensionKeys"
],
"Resource": [
"arn:aws:pi:us-east-1:123456789012:metrics/rds/db-ABC1DEFGHIJKL2MNOPQRSTUV3W"
],
"Condition": {
"ForAllValues:StringEquals": {
"pi:Dimensions": [
"db.sql_tokenized.id",
"db.sql_tokenized.statement"
]
}
}
}
]
}
```
The following is the response for the requested dimension:
```
// ListAvailableResourceDimensions API
// Request
{
"ServiceType": "RDS",
"Identifier": "db-ABC1DEFGHIJKL2MNOPQRSTUV3W",
"Metrics": [ "db.load" ],
"AuthorizedActions": ["DescribeDimensionKeys"]
}
// Response
{
"MetricDimensions": [ {
"Metric": "db.load",
"Groups": [
{
"Group": "db.sql_tokenized",
"Dimensions": [
{ "Identifier": "db.sql_tokenized.id" },
// { "Identifier": "db.sql_tokenized.db_id" }, // not included because not allows in the IAM Policy
{ "Identifier": "db.sql_tokenized.statement" }
]
}
] }
]
}
```
The following example specifies one allow and two deny access for the dimensions.
****
```
{
"Version":"2012-10-17",
"Statement": [
{
"Sid": "AllowToDiscoverDimensions",
"Effect": "Allow",
"Action": [
"pi:ListAvailableResourceDimensions"
],
"Resource": [
"arn:aws:pi:us-east-1:123456789012:metrics/rds/db-ABC1DEFGHIJKL2MNOPQRSTUV3W"
]
},
{
"Sid": "O01AllowAllWithoutSpecifyingDimensions",
"Effect": "Allow",
"Action": [
"pi:GetResourceMetrics",
"pi:DescribeDimensionKeys"
],
"Resource": [
"arn:aws:pi:us-east-1:123456789012:metrics/rds/db-ABC1DEFGHIJKL2MNOPQRSTUV3W"
]
},
{
"Sid": "O01DenyAppDimensionForAll",
"Effect": "Deny",
"Action": [
"pi:GetResourceMetrics",
"pi:DescribeDimensionKeys"
],
"Resource": [
"arn:aws:pi:us-east-1:123456789012:metrics/rds/db-ABC1DEFGHIJKL2MNOPQRSTUV3W"
],
"Condition": {
"ForAnyValue:StringEquals": {
"pi:Dimensions": [
"db.application.name"
]
}
}
},
{
"Sid": "O01DenySQLForGetResourceMetrics",
"Effect": "Deny",
"Action": [
"pi:GetResourceMetrics"
],
"Resource": [
"arn:aws:pi:us-east-1:123456789012:metrics/rds/db-ABC1DEFGHIJKL2MNOPQRSTUV3W"
],
"Condition": {
"ForAnyValue:StringEquals": {
"pi:Dimensions": [
"db.sql_tokenized.statement"
]
}
}
}
]
}
```
The following are the responses for the requested dimensions:
```
// ListAvailableResourceDimensions API
// Request
{
"ServiceType": "RDS",
"Identifier": "db-ABC1DEFGHIJKL2MNOPQRSTUV3W",
"Metrics": [ "db.load" ],
"AuthorizedActions": ["GetResourceMetrics"]
}
// Response
{
"MetricDimensions": [ {
"Metric": "db.load",
"Groups": [
{
"Group": "db.application",
"Dimensions": [
// removed from response because denied by the IAM Policy
// { "Identifier": "db.application.name" }
]
},
{
"Group": "db.sql_tokenized",
"Dimensions": [
{ "Identifier": "db.sql_tokenized.id" },
{ "Identifier": "db.sql_tokenized.db_id" },
// removed from response because denied by the IAM Policy
// { "Identifier": "db.sql_tokenized.statement" }
]
},
...
] }
]
}
```
```
// ListAvailableResourceDimensions API
// Request
{
"ServiceType": "RDS",
"Identifier": "db-ABC1DEFGHIJKL2MNOPQRSTUV3W",
"Metrics": [ "db.load" ],
"AuthorizedActions": ["DescribeDimensionKeys"]
}
// Response
{
"MetricDimensions": [ {
"Metric": "db.load",
"Groups": [
{
"Group": "db.application",
"Dimensions": [
// removed from response because denied by the IAM Policy
// { "Identifier": "db.application.name" }
]
},
{
"Group": "db.sql_tokenized",
"Dimensions": [
{ "Identifier": "db.sql_tokenized.id" },
{ "Identifier": "db.sql_tokenized.db_id" },
// allowed for DescribeDimensionKeys because our IAM Policy
// denies it only for GetResourceMetrics
{ "Identifier": "db.sql_tokenized.statement" }
]
},
...
] }
]
}
```
# Using tag-based access control for Performance Insights
You can control access to Performance Insights metrics using tags inherited from the parent DB instance. To control access to Performance Insights operations, use IAM policies. These policies can check the tags on your DB instance to determine permissions.
## How tags work with Performance Insights
Performance Insights automatically applies your DB instance tags to authorize Performance Insights metrics. When you add tags to your DB instance, you can immediately use those tags to control access to Performance Insights data.
+ To add or update tags for Performance Insights metrics, modify the tags on your DB instance.
+ To view tags for Performance Insights metrics, call `ListTagsForResource` on the Performance Insights metric resource. It will return the tags from the DB instance associated with the metric.
**Note**
The `TagResource` and `UntagResource` operations return an error if you try to use them directly on Performance Insights metrics.
## Creating tag-based IAM policies
To control access to Performance Insights operations, use the `aws:ResourceTag` condition key in your IAM policies. These policies check the tags on yourDB instance.
**Example**
This policy prevents access to Performance Insights metrics for production databases. The policy denies the `pi:GetResourceMetrics` operation in Performance Insights for any database resource tagged with `env:prod`.
```
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Deny",
"Action": "pi:GetResourceMetrics",
"Resource": "*",
"Condition": {
"StringEquals": {
"aws:ResourceTag/env": "prod"
}
}
}
]
}
```
# Analyzing metrics with the Performance Insights dashboard
**Important**
AWS has announced the end-of-life date for Performance Insights: June 30, 2026. After this date, Amazon RDS will no longer support the Performance Insights console experience, flexible retention periods (1-24 months), and their associated pricing. The Performance Insights API will continue to exist with no pricing changes. Costs for the Performance Insights API will appear in your AWS bill with the cost of CloudWatch Database Insights.
We recommend that you upgrade any DB instances using the paid tier of Performance Insights to the Advanced mode of Database Insights before June 30, 2026. For information about upgrading to the Advanced mode of Database Insights, see [Turning on the Advanced mode of Database Insights for Amazon RDS](USER_DatabaseInsights.TurningOnAdvanced.md).
If you take no action, DB instances using Performance Insights will default to using the Standard mode of Database Insights. With Standard mode of Database Insights, you might lose access to performance data history beyond 7 days and might not be able to use execution plans and on-demand analysis features in the Amazon RDS console. After June 30, 2026 only the Advanced mode of Database Insights will support execution plans and on-demand analysis.
With CloudWatch Database Insights, you can monitor database load for your fleet of databases and analyze and troubleshoot performance at scale. For more information about Database Insights, see [Monitoring Amazon RDS databases with CloudWatch Database Insights](USER_DatabaseInsights.md). For pricing information, see [Amazon CloudWatch Pricing](https://aws.amazon.com/cloudwatch/pricing/).
The Performance Insights dashboard contains database performance information to help you analyze and troubleshoot performance issues. On the main dashboard page, you can view information about the database load. You can "slice" DB load by dimensions such as wait events or SQL.
**Topics**
+ [
# Overview of the Performance Insights dashboard
](USER_PerfInsights.UsingDashboard.Components.md)
+ [
# Accessing the Performance Insights dashboard
](USER_PerfInsights.UsingDashboard.Opening.md)
+ [
# Analyzing DB load by wait events
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.md)
+ [
# Analyzing database performance for a period of time
](USER_PerfInsights.UsingDashboard.AnalyzePerformanceTimePeriod.md)
+ [
# Analyzing queries with the Top SQL tab in Performance Insights
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.md)
+ [
# Analyzing top Oracle PDB load
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.TopPDB.md)
+ [
# Analyzing execution plans using the Performance Insights dashboard for Amazon RDS
](USER_PerfInsights.UsingDashboard.AnalyzingPlans.md)
# Overview of the Performance Insights dashboard
The dashboard is the easiest way to interact with Performance Insights. The following example shows the dashboard for a PostgreSQL DB instance.
![\[Filter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_0b.png)
**Topics**
+ [
## Time range filter
](#USER_PerfInsights.UsingDashboard.Components.time-range)
+ [
## Counter metrics chart
](#USER_PerfInsights.UsingDashboard.Components.Countermetrics)
+ [
## Database load chart
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions)
+ [
## Top dimensions table
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable)
## Time range filter
By default, the Performance Insights dashboard shows DB load for the last hour. You can adjust this range to be as short as 5 minutes or as long as 2 years. You can also select a custom relative range.
![\[Performance Insights relative time\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-relative-time.png)
You can select an absolute range with a beginning and ending date and time. The following example shows the time range beginning at midnight on 9/25/24 and ending at 11:59 PM on 9/28/24.
![\[Performance Insights absolute time\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-absolute-time.png)
By default, the time zone for the Performance Insights dashboard is Coordinated Universal Time (UTC). You can also choose the local time zone.
![\[Select the local time zone for your Performance Insights dashboard\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-local-time-zone.png)
## Counter metrics chart
With counter metrics, you can customize the Performance Insights dashboard to include up to 10 additional graphs. These graphs show a selection of dozens of operating system and database performance metrics. You can correlate this information with DB load to help identify and analyze performance problems.
The **Counter metrics** chart displays data for performance counters. The default metrics depend on the DB engine:
+ MySQL and MariaDB – `db.SQL.Innodb_rows_read.avg`
+ Oracle – `db.User.user calls.avg`
+ Microsoft SQL Server – `db.Databases.Active Transactions(_Total).avg`
+ PostgreSQL – `db.Transactions.xact_commit.avg`
![\[Counter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/oracle_perf_insights_counters.png)
To change the performance counters, choose **Manage Metrics**. You can select multiple **OS metrics** or **Database metrics**, as shown in the following screenshot. To see details for any metric, hover over the metric name.
![\[Filter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_select_metrics.png)
For descriptions of the counter metrics that you can add for each DB engine, see [Performance Insights counter metrics](USER_PerfInsights_Counters.md).
## Database load chart
The **Database load** chart shows how the database activity compares to DB instance capacity as represented by the **Max vCPU** line. By default, the stacked line chart represents DB load as average active sessions per unit of time. The DB load is sliced (grouped) by wait states.
![\[Database load\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_2.png)
### DB load sliced by dimensions
You can choose to display load as active sessions grouped by any supported dimensions. The following table shows which dimensions are supported for the different engines.
| Dimension | Oracle | SQL Server | PostgreSQL | MySQL |
| --- | --- | --- | --- | --- |
| Host | Yes | Yes | Yes | Yes |
| SQL | Yes | Yes | Yes | Yes |
| User | Yes | Yes | Yes | Yes |
| Waits | Yes | Yes | Yes | Yes |
| Plans | Yes | No | No | No |
| Application | No | No | Yes | No |
| Database | No | No | Yes | Yes |
| Session type | No | No | Yes | No |
The following image shows the dimensions for a PostgreSQL DB instance.
![\[Filter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_2b.png)
### DB load details for a dimension item
To see details about a DB load item within a dimension, hover over the item name. The following image shows details for a SQL statement.
![\[Database load item details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_2c.png)
To see details for any item for the selected time period in the legend, hover over that item.
![\[Time period details for DB load\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_3.png)
## Top dimensions table
The Top dimensions table slices DB load by different dimensions. A dimension is a category or "slice by" for different characteristics of DB load. If the dimension is SQL, **Top SQL** shows the SQL statements that contribute the most to DB load.
![\[Top N dimensions\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_4c.png)
Choose any of the following dimension tabs.
| Tab | Description | Supported engines |
| --- | --- | --- |
| Top SQL | The SQL statements that are currently running | All |
| Top waits | The event for which the database backend is waiting | All |
| Top hosts | The host name of the connected client | All |
| Top users | The user logged in to the database | All |
| Top databases | The name of the database to which the client is connected | PostgreSQL, MySQL, MariaDB, and SQL Server only |
| Top applications | The name of the application that is connected to the database | PostgreSQL and SQL Server only |
| Top session types | The type of the current session | PostgreSQL only |
To learn how to analyze queries by using the **Top SQL** tab, see [Overview of the Top SQL tab](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.md#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL).
# Accessing the Performance Insights dashboard
Amazon RDS provides a consolidated view of Performance Insights and CloudWatch metrics in the Performance Insights dashboard.
To access the Performance Insights dashboard, use the following procedure.
**To view the Performance Insights dashboard in the AWS Management Console**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
For DB instances with Performance Insights turned on, you can also access the Performance Insights dashboard by choosing the **Sessions** item in the list of DB instances. Under **Current activity**, the **Sessions** item shows the database load in average active sessions over the last five minutes. The bar graphically shows the load. When the bar is empty, the DB instance is idle. As the load increases, the bar fills with blue. When the load passes the number of virtual CPUs (vCPUs) on the DB instance class, the bar turns red, indicating a potential bottleneck.
![\[Filter metrics\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_0a.png)
1. (Optional) Choose the date or time range in the upper right and specify a different relative or absolute time interval. You can now specify a time period, and generate a database performance analysis report. The report provides the identified insights and recommendations. For more information, see [Creating a performance analysis report in Performance Insights](USER_PerfInsights.UsingDashboard.AnalyzePerformanceTimePeriod.md).
![\[Filter metrics by time interval\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_0c.png)
In the following screenshot, the DB load interval is 5 hours.
![\[Set time interval to 5 hours\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_1.png)
1. (Optional) To zoom in on a portion of the DB load chart, choose the start time and drag to the end of the time period you want.
The selected area is highlighted in the DB load chart.
![\[DB load for a specified time interval\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_zoom_in.png)
When you release the mouse, the DB load chart zooms in on the selected AWS Region, and the **Top *dimensions*** table is recalculated.
![\[Zoom in on the selected DB load\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_zoom_in_b.png)
1. (Optional) To refresh your data automatically, select **Auto refresh**.
![\[Set automatic refresh\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_1b.png)
The Performance Insights dashboard automatically refreshes with new data. The refresh rate depends on the amount of data displayed:
+ 5 minutes refreshes every 10 seconds.
+ 1 hour refreshes every 5 minutes.
+ 5 hours refreshes every 5 minutes.
+ 24 hours refreshes every 30 minutes.
+ 1 week refreshes every day.
+ 1 month refreshes every day.
# Analyzing DB load by wait events
If the **Database load** chart shows a bottleneck, you can find out where the load is coming from. To do so, look at the top load items table below the **Database load** chart. Choose a particular item, like a SQL query or a user, to drill down into that item and see details about it.
DB load grouped by waits and top SQL queries is the default Performance Insights dashboard view. This combination typically provides the most insight into performance issues. DB load grouped by waits shows if there are any resource or concurrency bottlenecks in the database. In this case, the **SQL** tab of the top load items table shows which queries are driving that load.
Your typical workflow for diagnosing performance issues is as follows:
1. Review the **Database load** chart and see if there are any incidents of database load exceeding the **Max CPU** line.
1. If there is, look at the **Database load** chart and identify which wait state or states are primarily responsible.
1. Identify the digest queries causing the load by seeing which of the queries the **SQL** tab on the top load items table are contributing most to those wait states. You can identify these by the **DB Load by Wait** column.
1. Choose one of these digest queries in the **SQL** tab to expand it and see the child queries that it is composed of.
For example, in the dashboard following, **log file sync** waits account for most of the DB load. The **LGWR all worker groups** wait is also high. The **Top SQL** chart shows what is causing the **log file sync** waits: frequent `COMMIT` statements. In this case, committing less frequently will reduce DB load.
![\[log file sync errors\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_7.png)
# Analyzing database performance for a period of time
Analyze database performance with on-demand analysis by creating a performance analysis report for a period of time. View performance analysis reports to find performance issues, such as resource bottlenecks or changes in a query in your DB instance. The Performance Insights dashboard allows you to select a time period and create a performance analysis report. You can also add one or more tags to the report.
To use this feature, you must be using the paid tier retention period. For more information, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md)
The report is available in the **Performance analysis reports - new** tab to select and view. The report contains the insights, related metrics, and recommendations to resolve the performance issue. The report is available to view for the duration of Performance Insights retention period.
The report is deleted if the start time of the report analysis period is outside of the retention period. You can also delete the report before the retention period ends.
To detect the performance issues and generate the analysis report for your DB instance, you must turn on Performance Insights. For more information about turning on Performance Insights, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md).
For the region, DB engine, and instance class support information for this feature, see [Amazon RDS DB engine, Region, and instance class support for Performance Insights features](USER_PerfInsights.Overview.Engines.md#USER_PerfInsights.Overview.PIfeatureEngnRegSupport)
In the following sections, you can create, view, add tags, and delete a performance analysis report.
**Topics**
+ [
# Creating a performance analysis report in Performance Insights
](USER_PerfInsights.UsingDashboard.CreatingPerfAnlysisReport.md)
+ [
# Viewing a performance analysis report in Performance Insights
](USER_PerfInsights.UsingDashboard.ViewPerfAnalysisReport.md)
+ [
# Adding tags to a performance analysis report in Performance Insights
](USER_PerfInsights.UsingDashboard.ManagePerfAnalysisReportTags.md)
+ [
# Deleting a performance analysis report in Performance Insights
](USER_PerfInsights.UsingDashboard.DeletePerfAnalysisReport.md)
# Creating a performance analysis report in Performance Insights
You can create a performance analysis report for a specific period in the Performance Insights dashboard. You can select a time period and add one or more tags to the analysis report.
The analysis period can range from 5 minutes to 6 days. There must be at least 24 hours of performance data before the analysis start time.
For the region, DB engine, and instance class support information for this feature, see [Amazon RDS DB engine, Region, and instance class support for Performance Insights features](USER_PerfInsights.Overview.Engines.md#USER_PerfInsights.Overview.PIfeatureEngnRegSupport)
**To create a performance analysis report for a time period**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
1. Choose **Analyze performance** in **Database load** section on the Performance Insights dashboard.
The fields to set the time period and add one or more tags to the performance analysis report are displayed.
![\[Performance Insights dashboard showing fields to create analysis report\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_CreateAnalysisReport.png)
1. Choose the time period. If you set a time period in the **Relative range** or **Absolute range** in the upper right, you can only enter or select the analysis report date and time within this time period. If you select the analysis period outside of this time period, an error message displays.
To set the time period, you can do any of the following:
+ Press and drag any of the sliders on the DB load chart.
The **Performance analysis period** box displays the selected time period and DB load chart highlights the selected time period.
+ Choose the **Start date**, **Start time**, **End date**, and **End time** in the **Performance analysis period** box.
![\[Performance Insights dashboard with analysis period selected\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_CreateAnalysisRep_TimePeriod.png)
1. (Optional) Enter **Key** and **Value-*optional*** to add a tag for the report.
![\[Performance Insights dashboard with fields to add a new tag\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_CreateAnalysisRep_AddTag.png)
1. Choose **Analyze performance**.
A banner displays a message whether the report generation is successful or failed. The message also provides the link to view the report.
The following example shows the banner with the report creation successful message.
![\[Analysis report creation successful message banner\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_CreateAnaysisRep_SuccessMsg.png)
The report is available to view in **Performance analysis reports - new** tab.
You can create a performance analysis report using the AWS CLI. For an example on how to create a report using AWS CLI, see [Creating a performance analysis report for a time period](USER_PerfInsights.API.Examples.md#USER_PerfInsights.API.Examples.CreatePerfAnalysisReport).
# Viewing a performance analysis report in Performance Insights
The **Performance analysis reports - new** tab lists all the reports that are created for the DB instance. The following are displayed for each report:
+ **ID**: Unique identifier of the report.
+ **Name**: Tag key added to the report.
+ **Report creation time**: Time you created the report.
+ **Analysis start time**: Start time of the analysis in the report.
+ **Analysis end time**: End time of the analysis in the report.
**To view a performance analysis report**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance for which you want to view the analysis report.
1. Scroll down and choose **Performance analysis reports - new** tab in the Performance Insights dashboard.
All the analysis reports for the different time periods are displayed.
1. Choose **ID** of the report you want to view.
The DB load chart displays the entire analysis period by default if more than one insight is identified. If the report has identified one insight then the DB load chart displays the insight by default.
The dashboard also lists the tags for the report in the **Tags** section.
The following example shows the entire analysis period for the report.
![\[DB load chart showing entire analysis report period\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_EntireAnalysisRep.png)
1. Choose the insight in the **Database load insights** list you want to view if more than one insight is identified in the report.
The dashboard displays the insight message, DB load chart highlighting the time period of the insight, analysis and recommendations, and the list of report tags.
The following example shows the DB load insight in the report.
![\[DB load chart showing insight in the report\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_AnalysisRepInsight_chart.png)
![\[Report insight analysis and recommendation section\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_AnalysisRepInsight_Recommendations.png)
# Adding tags to a performance analysis report in Performance Insights
You can add a tag when you create or view a report. You can add up to 50 tags for a report.
You need permissions to add the tags. For more information about the access policies for Performance Insights, see [Configuring access policies for Performance Insights](USER_PerfInsights.access-control.md)
To add one or more tags while creating a report, see step 6 in the procedure [Creating a performance analysis report in Performance Insights](USER_PerfInsights.UsingDashboard.CreatingPerfAnlysisReport.md).
**To add one or more tags when viewing a report**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
The Performance Insights dashboard appears for the DB instance.
1. Scroll down and choose **Performance analysis reports - new** tab.
1. Choose the report for which you want to add the tags.
The dashboard displays the report.
1. Scroll down to **Tags** and choose **Manage tags**.
1. Choose **Add new tag**.
1. Enter the **Key** and **Value - *optional***, and choose **Add new tag**.
The following example provides the option to add a new tag for the selected report.
![\[Manage Tags window to add new tags to the report\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_AddTag_ManageTags.png)
A new tag is created for the report.
The list of tags for the report is displayed in the **Tags** section on the dashboard. If you want to remove a tag from the report, choose **Remove** next to the tag.
# Deleting a performance analysis report in Performance Insights
You can delete a report from the list of reports displayed in the **Performance analysis reports** tab or while viewing a report.
**To delete a report**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
The Performance Insights dashboard appears for the DB instance.
1. Scroll down and choose **Performance analysis reports - new** tab.
1. Select the report you want to delete and choose **Delete** in the upper right.
![\[Performance Insights dashboard to delete with a report selected for deletion\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/PI_DeleteAnalysisRep.png)
A confirmation window is displayed. The report is deleted after you choose confirm.
1. (Optional) Choose **ID** of the report you want to delete.
In the report page, choose **Delete** in the upper right.
A confirmation window is displayed. The report is deleted after you choose confirm.
# Analyzing queries with the Top SQL tab in Performance Insights
In the Amazon RDS Performance Insights dashboard, you can find information about running and recent queries in the **Top SQL** tab in the **Top dimensions** table. You can use this information to tune your queries.
**Topics**
+ [
## Overview of the Top SQL tab
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL)
+ [
# Accessing more SQL text in the Performance Insights dashboard
](USER_PerfInsights.UsingDashboard.SQLTextSize.md)
+ [
# Viewing SQL statistics in the Performance Insights dashboard
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.AnalyzingSQLLevel.md)
## Overview of the Top SQL tab
By default, the **Top SQL** tab shows the 25 queries that are contributing the most to DB load. To help tune your queries, you can analyze information such as the query text and SQL statistics. You can also choose the statistics that you want to appear in the **Top SQL** tab.
**Topics**
+ [
### SQL text
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL.text)
+ [
### SQL statistics
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL.statistics)
+ [
### Load by waits (AAS)
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL.Load-by-waits)
+ [
### View SQL information
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL.SQL-information)
+ [
### Choose statistics preferences
](#USER_PerfInsights.UsingDashboard.Components.AvgActiveSessions.TopLoadItemsTable.TopSQL.Preferences)
### SQL text
By default, each row in the **Top SQL** table shows 500 bytes of text for each statement.
![\[SQL text\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/sql-text-oracle.png)
To learn how to see more than the default 500 bytes of SQL text, see [Accessing more SQL text in the Performance Insights dashboard](USER_PerfInsights.UsingDashboard.SQLTextSize.md).
A *SQL digest* is a composite of multiple actual queries that are structurally similar but might have different literal values. The digest replaces hardcoded values with a question mark. For example, a digest might be `SELECT * FROM emp WHERE lname= ?`. This digest might include the following child queries:
```
SELECT * FROM emp WHERE lname = 'Sanchez'
SELECT * FROM emp WHERE lname = 'Olagappan'
SELECT * FROM emp WHERE lname = 'Wu'
```
To see the literal SQL statements in a digest, select the query, and then choose the plus symbol (\$1). In the following example, the selected query is a digest.
![\[Selected SQL digest\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_4b.png)
**Note**
A SQL digest groups similar SQL statements, but doesn't redact sensitive information.
Performance Insights can show Oracle SQL text as **Unknown**. The text has this status in the following situations:
+ An Oracle database user other than `SYS` is active but not currently executing SQL. For example, when a parallel query completes, the query coordinator waits for helper processes to send their session statistics. For the duration of the wait, the query text shows **Unknown**.
+ For an RDS for Oracle instance on Standard Edition 2, Oracle Resource Manager limits the number of parallel threads. The background process doing this work causes the query text to show as **Unknown**.
### SQL statistics
*SQL statistics* are performance-related metrics about SQL queries. For example, Performance Insights might show executions per second or rows processed per second. Performance Insights collects statistics for only the most common queries. Typically, these match the top queries by load shown in the Performance Insights dashboard.
Every line in the **Top SQL** table shows relevant statistics for the SQL statement or digest, as shown in the following example.
![\[Top SQL\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_4.png)
Performance Insights can report `0.00` and `-` (unknown) for SQL statistics. This situation occurs under the following conditions:
+ Only one sample exists. For example, Performance Insights calculates rates of change for RDS PostgreSQL queries based on multiple samples from the `pg_stat_statements` view. When a workload runs for a short time, Performance Insights might collect only one sample, which means that it can't calculate a rate of change. The unknown value is represented with a dash (`-`).
+ Two samples have the same values. Performance Insights can't calculate a rate of change because no change has occurred, so it reports the rate as `0.00`.
+ An RDS PostgreSQL statement lacks a valid identifier. PostgreSQL creates a identifier for a statement only after parsing and analysis. Thus, a statement can exist in the PostgreSQL internal in-memory structures with no identifier. Because Performance Insights samples internal in-memory structures once per second, low-latency queries might appear for only a single sample. If the query identifier isn't available for this sample, Performance Insights can't associate this statement with its statistics. The unknown value is represented with a dash (`-`).
For a description of the SQL statistics for the Amazon RDS engines, see [SQL statistics for Performance Insights](sql-statistics.md).
### Load by waits (AAS)
In **Top SQL**, the **Load by waits (AAS)** column illustrates the percentage of the database load associated with each top load item. This column reflects the load for that item by whatever grouping is currently selected in the **DB Load Chart**. For more information about Average active sessions (AAS), see [Average active sessions](USER_PerfInsights.Overview.ActiveSessions.md#USER_PerfInsights.Overview.ActiveSessions.AAS).
For example, you might group the **DB load** chart by wait states. You examine SQL queries in the top load items table. In this case, the **DB Load by Waits** bar is sized, segmented, and color-coded to show how much of a given wait state that query is contributing to. It also shows which wait states are affecting the selected query.
![\[DB load by waits\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_6.png)
### View SQL information
In the **Top SQL** table, you can open a statement to view its information. The information appears in the bottom pane.
![\[Top SQL table with literal query selected\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-sql-ids-open.png)
The following types of identifiers (IDs) that are associated with SQL statements:
+ **Support SQL ID** – A hash value of the SQL ID. This value is only for referencing a SQL ID when you are working with AWS Support. AWS Support doesn't have access to your actual SQL IDs and SQL text.
+ **Support Digest ID** – A hash value of the digest ID. This value is only for referencing a digest ID when you are working with AWS Support. AWS Support doesn't have access to your actual digest IDs and SQL text.
### Choose statistics preferences
You can control the statistics displayed in the **Top SQL** tab by choosing the **Preferences** icon.
![\[Statistics preferences\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-sql-ids-preferences-icon.png)
When you choose the **Preferences** icon, the **Preferences** window opens. The following screenshot is an example of the **Preferences** window.
![\[Preferences window\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-sql-ids-preferences.png)
To enable the statistics that you want to appear in the **Top SQL** tab, use your mouse to scroll to the bottom of the window, and then choose **Continue**.
For more information about per-second or per-call statistics for the Amazon RDS engines, see the engine specific SQL statistics section in [SQL statistics for Performance Insights](sql-statistics.md)
# Accessing more SQL text in the Performance Insights dashboard
By default, each row in the **Top SQL** table shows 500 bytes of SQL text for each SQL statement.
![\[500 bytes of SQL\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-top-sql-bytes.png)
When a SQL statement exceeds 500 bytes, you can view more text in the **SQL text** section below the **Top SQL** table. In this case, the maximum length for the text displayed in **SQL text** is 4 KB. This limit is introduced by the console and is subject to the limits set by the database engine. To save the text shown in **SQL text**, choose **Download**.
**Topics**
+ [
## Text size limits for Amazon RDS engines
](#sql-text-engine-limits)
+ [
# Setting the SQL text limit for Amazon RDS for PostgreSQL DB instances
](USER_PerfInsights.UsingDashboard.SQLTextLimit.md)
+ [
# Viewing and downloading SQL text in the Performance Insights dashboard
](view-download-text.md)
## Text size limits for Amazon RDS engines
When you download SQL text, the database engine determines its maximum length. You can download SQL text up to the following per-engine limits.
| DB engine | Maximum length of downloaded text |
| --- | --- |
| Amazon RDS for MySQL and MariaDB | The length is fixed at 4,096 bytes when the Performance Schema is enabled. If the Performance Schema isn't enabled, the length is fixed at 65,535 bytes. |
| Amazon RDS for Microsoft SQL Server | 4,096 characters |
| Amazon RDS for Oracle | 1,000 bytes |
The **SQL text** section of the Performance Insights console displays up to the maximum that the engine returns. For example, if MySQL returns at most 1 KB to Performance Insights, it can only collect and show 1 KB, even if the original query is larger. Thus, when you view the query in **SQL text** or download it, Performance Insights returns the same number of bytes.
If you use the AWS CLI or API, Performance Insights doesn't have the 4 KB limit enforced by the console. `DescribeDimensionKeys` and `GetResourceMetrics` return at most 500 bytes.
**Note**
`GetDimensionKeyDetails` returns the full query, but the size is subject to the engine limit.
# Setting the SQL text limit for Amazon RDS for PostgreSQL DB instances
Amazon RDS for PostgreSQL handles text differently. You can set the text size limit with the DB instance parameter `track_activity_query_size`. This parameter has the following characteristics:
Default text size
On Amazon RDS for PostgreSQL version 9.6, the default setting for the `track_activity_query_size` parameter is 1,024 bytes. On Amazon RDS for PostgreSQL version 10 or higher, the default is 4,096 bytes.
Maximum text size
The limit for `track_activity_query_size` is 102,400 bytes for Amazon RDS for PostgreSQL version 12 and lower. The maximum is 1 MB for version 13 and higher.
If the engine returns 1 MB to Performance Insights, the console displays only the first 4 KB. If you download the query, you get the full 1 MB. In this case, viewing and downloading return different numbers of bytes. For more information about the `track_activity_query_size` DB instance parameter, see [Run-time Statistics](https://www.postgresql.org/docs/current/runtime-config-statistics.html) in the PostgreSQL documentation.
To increase the SQL text size, increase the `track_activity_query_size` limit. To modify the parameter, change the parameter setting in the parameter group that is associated with the Amazon RDS for PostgreSQL DB instance.
**To change the setting when the instance uses the default parameter group**
1. Create a new DB instance parameter group for the appropriate DB engine and DB engine version.
1. Set the parameter in the new parameter group.
1. Associate the new parameter group with the DB instance.
For information about setting a DB instance parameter, see [Modifying parameters in a DB parameter group in Amazon RDS](USER_WorkingWithParamGroups.Modifying.md).
# Viewing and downloading SQL text in the Performance Insights dashboard
In the Performance Insights dashboard, you can view or download SQL text.
**To view more SQL text in the Performance Insights dashboard**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, choose **Performance Insights**.
1. Choose a DB instance.
1. Scroll down to the **Top SQL** tab in the Performance Insights dashboard.
1. Choose the plus sign to expand a SQL digest and choose one of the digest's child queries.
SQL statements with text larger than 500 bytes look similar to the following image.
![\[SQL statements with large text\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-large-text-1.png)
1. Scroll down to the **SQL text** tab.
![\[SQL information section shows more of the SQL text\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-large-text-2.png)
The Performance Insights dashboard can display up to 4,096 bytes for each SQL statement.
1. (Optional) Choose **Copy** to copy the displayed SQL statement, or choose **Download** to download the SQL statement to view the SQL text up to the DB engine limit.
**Note**
To copy or download the SQL statement, disable pop-up blockers.
# Viewing SQL statistics in the Performance Insights dashboard
In the Performance Insights dashboard, SQL statistics are available in the **Top SQL** tab of the **Database load** chart.
**To view SQL statistics**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, choose **Performance Insights**.
1. At the top of the page, choose the database whose SQL statistics you want to see.
1. Scroll to the bottom of the page and choose the **Top SQL** tab.
1. Choose an individual statement or digest query.
![\[Viewing metrics for running queries\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_per_sql_sql.png)
1. Choose which statistics to display by choosing the gear icon in the upper-right corner of the chart. For descriptions of the SQL statistics for the Amazon RDS engines, see [SQL statistics for Performance Insights](sql-statistics.md).
The following example shows the statistics preferences for Oracle DB instances.
![\[Preferences for metrics for running queries for Oracle DB instances\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_per_sql_pref_oracle.png)
The following example shows the preferences for MariaDB and MySQL DB instances.
![\[Preferences for metrics for running queries for MariaDB and MySQL DB instances.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_per_sql_pref_ams.png)
1. Choose Save to save your preferences.
The **Top SQL** table refreshes.
The following example shows statistics for an Oracle SQL query.
![\[Statistics for a SQL query\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_per_sql_stats_oracle.png)
# Analyzing top Oracle PDB load
When analyzing the load on an Oracle container DB (CDB), you might want to identify which pluggable databases (PDBs) contribute the most to DB load. You might also want to compare the performance of individual PDBs that are running similar queries to fine tune performance. For more information about Oracle CDBs, see [RDS for Oracle database architecture](oracle-multi-architecture.md).
In the Amazon RDS Performance Insights dashboard, you can find information about pluggable databases (PDBs) under **Top PDB** tab in the **Dimensions** tab.
For the region, DB engine, and instance class support information for this feature, see [Amazon RDS DB engine, Region, and instance class support for Performance Insights features](USER_PerfInsights.Overview.Engines.md#USER_PerfInsights.Overview.PIfeatureEngnRegSupport).
**To analyze Top PDB load in an Oracle CDB**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the left navigation pane, select **Performance Insights**.
1. Choose an Oracle CDB instance.
The Performance Insights dashboard appears for the DB instance.
1. In the **Database load (DB load)** section, choose **Pluggable database (PDB)** next to Slice by.
The Average active sessions chart shows the PDB with the highest load. The PDB identifiers appear to the right of the color-coded squares. Each identifier uniquely identifies a PDB.
![\[Average active sessions chart for PDB load\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_topPDB_AAS.png)
1. Scroll down to the **Top SQL** tab.
In the following example, you can see the same SQL query and the load it drives to multiple PDBs.
![\[Same SQL query load for multiple PDBs\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_topPDB_ex1.png)
In the following example, a single PDB is handling higher load than other PDBs in the CDB.
![\[High SQL query load for PDB\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf_insights_topPDB_ex2.png)
For more information about Oracle CDBs, see [ CDBs and PDBs](https://docs.oracle.com/en/database/oracle/oracle-database/21/cncpt/CDBs-and-PDBs.html#GUID-FC2EB562-ED31-49EF-8707-C766B6FE66B8).
# Analyzing execution plans using the Performance Insights dashboard for Amazon RDS
In the Amazon RDS Performance Insights dashboard, you can find information about execution plans for Oracle and SQL Server DB instances. You can use this information to know which plans contribute the most to DB load.
To analyze Oracle or SQL Server execution plans, see the following topics.
**Analyzing execution plans**
+ [Analyzing Oracle execution plans using the Performance Insights dashboard for Amazon RDS](USER_PerfInsights.UsingDashboard.AccessPlans.md)
+ [Analyzing SQL Server execution plans using the Performance Insights dashboard for Amazon RDS](USER_PerfInsights.UsingDashboard.AccessPlansSqlServer.md)
## Overview of analyzing execution plans for Amazon RDS
You can use the Amazon RDS Performance Insights dashboard to know which plans contribute the most to DB load for Oracle and SQL Server DB instances.
For example, the top SQL statements at a given time might be using the plans shown in the following table.
****
| Top SQL | Plan |
| --- | --- |
| SELECT SUM(amount\$1sold) FROM sales WHERE prod\$1id = 10 | Plan A |
| SELECT SUM(amount\$1sold) FROM sales WHERE prod\$1id = 521 | Plan B |
| SELECT SUM(s\$1total) FROM sales WHERE region = 10 | Plan A |
| SELECT \$1 FROM emp WHERE emp\$1id = 1000 | Plan C |
| SELECT SUM(amount\$1sold) FROM sales WHERE prod\$1id = 72 | Plan A |
With the plan feature of Performance Insights, you can do the following:
+ Find out which plans are used by the top SQL queries.
For example, you might find out that most of the DB load is generated by queries using plan A and plan B, with only a small percentage using plan C.
+ Compare different plans for the same query.
In the preceding example, three queries are identical except for the product ID. Two queries use plan A, but one query uses plan B. To see the difference in the two plans, you can use Performance Insights.
+ Find out when a query switched to a new plan.
You might see that a query used plan A and then switched to plan B at a certain time. Was there a change in the database at this point? For example, if a table is empty, the optimizer might choose a full table scan. If the table is loaded with a million rows, the optimizer might switch to an index range scan.
+ Drill down to the specific steps of a plan with the highest cost.
For example, the for a long-running query might show a missing a join condition in an equi-join. This missing condition forces a Cartesian join, which joins all rows of two tables.
You can perform the preceding tasks by using the plan capture feature of Performance Insights. Just as you can slice queries by wait events and top SQL, you can slice them by the plan dimension.
# Analyzing Oracle execution plans using the Performance Insights dashboard for Amazon RDS
When analyzing DB load on an Oracle Database, you might want to know which plans are contributing the most to DB load. You can determine which plans are contributing the most to DB load by using the plan capture feature of Performance Insights.
**To analyze Oracle execution plans using the console**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, choose **Performance Insights**.
1. Choose an Oracle DB instance. The Performance Insights dashboard is displayed for that DB instance.
1. In the **Database load (DB load)** section, choose **Plans** next to **Slice by**.
The Average active sessions chart shows the plans used by your top SQL statements. The plan hash values appear to the right of the color-coded squares. Each hash value uniquely identifies a plan.
![\[Slice by plans\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-slice-by-plans.png)
1. Scroll down to the **Top SQL** tab.
In the following example, the top SQL digest has two plans. You can tell that it's a digest by the question mark in the statement.
![\[Choose a digest plan\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/top-sql-plans-unselected.png)
1. Choose the digest to expand it into its component statements.
In the following example, the `SELECT` statement is a digest query. The component queries in the digest use two different plans. The colors of the plans correspond to the database load chart. The total number of plans in the digest is shown in the second column.
![\[Choose a digest plan\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-digest-plan.png)
1. Scroll down and choose two **Plans** to compare from **Plans for digest query** list.
You can view either one or two plans for a query at a time. The following screenshot compares the two plans in the digest, with hash 2032253151 and hash 1117438016. In the following example, 62% of the average active sessions running this digest query are using the plan on the left, whereas 38% are using the plan on the right.
![\[Compare the plans side by side\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-compare-plan.png)
In this example, the plans differ in an important way. Step 2 in plan 2032253151 uses an index scan, whereas plan 1117438016 uses a full table scan. For a table with a large number of rows, a query of a single row is almost always faster with an index scan.
![\[Compare the plans side by side\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-table-access.png)
1. (Optional) Choose **Copy** to copy the plan to the clipboard, or **Download** to save the plan to your hard drive.
# Analyzing SQL Server execution plans using the Performance Insights dashboard for Amazon RDS
When analyzing DB load on a SQL Server Database, you might want to know which plans are contributing the most to DB load. You can determine which plans are contributing the most to DB load by using the plan capture feature of Performance Insights.
**To analyze SQL Server execution plans using the console**
1. Open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, choose **Performance Insights**.
1. Choose a SQL Server DB instance. The Performance Insights dashboard is displayed for that DB instance.
1. In the **Database load (DB load)** section, choose **Plans** next to **Slice by**.
The Average active sessions chart shows the plans used by your top SQL statements. The plan hash values appear to the right of the color-coded squares. Each hash value uniquely identifies a plan.
![\[Slice by plans\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-slice-by-plans-sqlserver.png)
1. Scroll down to the **Top SQL** tab.
In the following example, the top SQL digest has three plans. The presence of a question mark in the SQL statement indicates that the statement is a digest. To view the full SQL statement, choose a value in the **SQL statements** column.
![\[Choose a digest plan\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/top-sql-plans-unselected-sqlserver.png)
1. Choose the digest to expand it into its component statements.
In the following example, the `SELECT` statement is a digest query. The component queries in the digest use three different execution plans. The colors assigned to the plans correspond to the database load chart.
![\[Choose a digest plan\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-digest-plan-sqlserver.png)
1. Scroll down and choose two **Plans** to compare from **Plans for digest query** list.
You can view either one or two plans for a query at a time. The following screenshot compares two plans in the digest. In the following example, 40% of the average active sessions running this digest query are using the plan on the left, whereas 28% are using the plan on the right.
![\[Compare the plans side by side\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-compare-plan-sqlserver.png)
In the previous example, the plans differ in an important way. Step 2 in the plan on the left uses an table scan, whereas the plan on the right uses a clustered index scan. For a table with a large number of rows, a query retrieving a single row is almost always faster with a clustered index scan.
1. (Optional) Choose the **Settings** icon on the Plan Details table to customize the visibility and order of columns. The following screenshot shows the Plan Details table with the **Output list** column as the second column.
![\[Customize the visibility and order of columns in the Plan Details table\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/pi-plan-fields-sql-server.png)
1. (Optional) Choose **Copy** to copy the plan to the clipboard, or **Download** to save the plan to your hard drive.
**Note**
Performance Insights displays estimated execution plans using a hierarchical tree table. The table includes the partial execution information for each statement. For more information about the columns in the Plan Details table, see [SET SHOWPLAN\$1ALL](https://learn.microsoft.com/en-us/sql/t-sql/statements/set-showplan-all-transact-sql) in the SQL Server documentation. To display the full execution information for an estimated execution plan, choose **Download** to download the plan and then upload the plan to SQL Server Management Studio. For more information about displaying an estimated execution plan using SQL Server Management Studio, see [Display an Estimated Execution Plan](https://learn.microsoft.com/en-us/sql/relational-databases/performance/display-the-estimated-execution-plan) in the SQL Server documentation.
# Viewing Performance Insights proactive recommendations
Amazon RDS Performance Insights monitors specific metrics and automatically creates thresholds by analyzing what levels might be potentially problematic for a specified resource. When the new metric values cross a predefined threshold over a given period of time, Performance Insights generates a proactive recommendation. This recommendation helps to prevent future database performance impact. To receive these proactive recommendations, you must turn on Performance Insights with a paid tier retention period.
For more information about turning on Performance Insights, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md). For information about pricing and data retention for Performance Insights, see [Pricing and data retention for Performance Insights](USER_PerfInsights.Overview.cost.md).
To find out the regions, DB engines, and instance classes supported for the proactive recommendations, see [Amazon RDS DB engine, Region, and instance class support for Performance Insights features](USER_PerfInsights.Overview.Engines.md#USER_PerfInsights.Overview.PIfeatureEngnRegSupport).
You can view the detailed analysis and recommended investigations of proactive recommendations in the recommendation details page.
For more information about recommendations, see [Recommendations from Amazon RDS](monitoring-recommendations.md).
**To view the detailed analysis of a proactive recommendation**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. In the navigation pane, do any of the following:
+ Choose **Recommendations**.
The **Recommendations** page displays a list of recommendations sorted by the severity for all the resources in your account.
+ Choose **Databases** and then choose **Recommendations** for a resource in the databases page.
The **Recommendations** tab displays the recommendations and its details for the selected resource.
1. Find a proactive recommendation and choose **View details**.
The recommendation details page appears. The title provides the name of the affected resource with the issue detected and the severity.
The following are the components on the recommendation details page:
+ **Recommendation summary** – The detected issue, recommendation and issue status, issue start and end time, recommendation modified time, and the engine type.
![\[Recommendation details page for proactive recommendation showing the Recommendation summary section in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/RecommendationProactive-RecSummary.png)
+ **Metrics** – The graphs of the detected issue. Each graph displays a threshold determined by the resource's baseline behavior and data of the metric reported from the issue start time.
![\[Recommendation details page for proactive recommendation showing the Metrics section in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/RecommedationProactive_Metrics.png)
+ **Analysis and recommendations** – The recommendation and the reason for the suggested recommendation.
![\[Recommendation details page for proactive recommendation showing the Analysis and recommendations section in the console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/ProactiveRecommendation-AnalysisAndRec.png)
You can review the cause of the issue and then perform the suggested recommended actions to fix the issue, or choose **Dismiss** in the upper right to dismiss the recommendation.
# Retrieving metrics with the Performance Insights API for Amazon RDS
When Performance Insights is turned on, the API provides visibility into instance performance. Amazon CloudWatch Logs provides the authoritative source for vended monitoring metrics for AWS services.
Performance Insights offers a domain-specific view of database load measured as average active sessions (AAS). This metric appears to API consumers as a two-dimensional time-series dataset. The time dimension of the data provides DB load data for each time point in the queried time range. Each time point decomposes overall load in relation to the requested dimensions, such as `SQL`, `Wait-event`, `User`, or `Host`, measured at that time point.
Amazon RDS Performance Insights monitors your Amazon RDS DB instance so that you can analyze and troubleshoot database performance. One way to view Performance Insights data is in the AWS Management Console. Performance Insights also provides a public API so that you can query your own data. You can use the API to do the following:
+ Offload data into a database
+ Add Performance Insights data to existing monitoring dashboards
+ Build monitoring tools
To use the Performance Insights API, enable Performance Insights on one of your Amazon RDS DB instances. For information about enabling Performance Insights, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md). For more information about the Performance Insights API, see the [Amazon RDS Performance Insights API Reference](https://docs.aws.amazon.com/performance-insights/latest/APIReference/Welcome.html).
The Performance Insights API provides the following operations.
****
| Performance Insights action | AWS CLI command | Description |
| --- | --- | --- |
| [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_CreatePerformanceAnalysisReport.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_CreatePerformanceAnalysisReport.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/CreatePerformanceAnalysisReport.html](https://docs.aws.amazon.com/cli/latest/reference/pi/CreatePerformanceAnalysisReport.html) | Creates a performance analysis report for a specific time period for the DB instance. The result is `AnalysisReportId` which is the unique identifier of the report. |
| [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DeletePerformanceAnalysisReport.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DeletePerformanceAnalysisReport.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/DeletePerformanceAnalysisReport.html](https://docs.aws.amazon.com/cli/latest/reference/pi/DeletePerformanceAnalysisReport.html) | Deletes a performance analysis report. |
| [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DescribeDimensionKeys.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DescribeDimensionKeys.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/describe-dimension-keys.html](https://docs.aws.amazon.com/cli/latest/reference/pi/describe-dimension-keys.html) | Retrieves the top N dimension keys for a metric for a specific time period. |
| [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetDimensionKeyDetails.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetDimensionKeyDetails.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/get-dimension-key-details.html](https://docs.aws.amazon.com/cli/latest/reference/pi/get-dimension-key-details.html) | Retrieves the attributes of the specified dimension group for a DB instance or data source. For example, if you specify a SQL ID, and if the dimension details are available, `GetDimensionKeyDetails` retrieves the full text of the dimension `db.sql.statement` associated with this ID. This operation is useful because `GetResourceMetrics` and `DescribeDimensionKeys` don't support retrieval of large SQL statement text. |
| [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetPerformanceAnalysisReport.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetPerformanceAnalysisReport.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/GetPerformanceAnalysisReport.html](https://docs.aws.amazon.com/cli/latest/reference/pi/GetPerformanceAnalysisReport.html) | Retrieves the report including the insights for the report. The result includes the report status, report ID, report time details, insights, and recommendations. |
| [GetResourceMetadata](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetResourceMetadata.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/get-resource-metadata.html](https://docs.aws.amazon.com/cli/latest/reference/pi/get-resource-metadata.html) | Retrieve the metadata for different features. For example, the metadata might indicate that a feature is turned on or off on a specific DB instance. |
| [https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetResourceMetrics.html](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_GetResourceMetrics.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/get-resource-metrics.html](https://docs.aws.amazon.com/cli/latest/reference/pi/get-resource-metrics.html) | Retrieves Performance Insights metrics for a set of data sources over a time period. You can provide specific dimension groups and dimensions, and provide aggregation and filtering criteria for each group. |
| [ListAvailableResourceDimensions](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_ListAvailableResourceDimensions.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/list-available-resource-dimensions.html](https://docs.aws.amazon.com/cli/latest/reference/pi/list-available-resource-dimensions.html) | Retrieve the dimensions that can be queried for each specified metric type on a specified instance. |
| [ListAvailableResourceMetrics](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_ListAvailableResourceMetrics.html) | [https://docs.aws.amazon.com/cli/latest/reference/pi/list-available-resource-metrics.html](https://docs.aws.amazon.com/cli/latest/reference/pi/list-available-resource-metrics.html) | Retrieve all available metrics of the specified metric types that can be queried for a specified DB instance. |
| `[ListPerformanceAnalysisReports](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_ListPerformanceAnalysisReports.html)` | [https://docs.aws.amazon.com/cli/latest/reference/pi/list-performance-analysis-reports.html](https://docs.aws.amazon.com/cli/latest/reference/pi/list-performance-analysis-reports.html) | Retrieves all the analysis reports available for the DB instance. The reports are listed based on the start time of each report. |
| `[ListTagsForResource](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_ListTagsForResource.html)` | [https://docs.aws.amazon.com/cli/latest/reference/pi/list-tags-for-resource.html](https://docs.aws.amazon.com/cli/latest/reference/pi/list-tags-for-resource.html) | Lists all the metadata tags added to the resource. The list includes the name and value of the tag. |
| `[TagResource](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_TagResource.html)` | [https://docs.aws.amazon.com/cli/latest/reference/pi/tag-resource.html](https://docs.aws.amazon.com/cli/latest/reference/pi/tag-resource.html) | Adds metadata tags to the Amazon RDS resource. The tag includes a name and a value. |
| `[UntagResource](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_UntagResource.html)` | [https://docs.aws.amazon.com/cli/latest/reference/pi/untag-resource.html](https://docs.aws.amazon.com/cli/latest/reference/pi/untag-resource.html) | Removes the metadata tag from the resource. |
For more information about retrieving time-series metrics and AWS CLI examples for Performance Insights, see the following topics.
**Topics**
+ [
# Retrieving time-series metrics for Performance Insights
](USER_PerfInsights.API.TimeSeries.md)
+ [
# AWS CLI examples for Performance Insights
](USER_PerfInsights.API.Examples.md)
# Retrieving time-series metrics for Performance Insights
The `GetResourceMetrics` operation retrieves one or more time-series metrics from the Performance Insights data. `GetResourceMetrics` requires a metric and time period, and returns a response with a list of data points.
For example, the AWS Management Console uses `GetResourceMetrics` to populate the **Counter Metrics** chart and the **Database Load** chart, as seen in the following image.
![\[Counter Metrics and Database Load charts\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-api-charts.png)
All metrics returned by `GetResourceMetrics` are standard time-series metrics, with the exception of `db.load`. This metric is displayed in the **Database Load** chart. The `db.load` metric is different from the other time-series metrics because you can break it into subcomponents called *dimensions*. In the previous image, `db.load` is broken down and grouped by the waits states that make up the `db.load`.
**Note**
`GetResourceMetrics` can also return the `db.sampleload` metric, but the `db.load` metric is appropriate in most cases.
For information about the counter metrics returned by `GetResourceMetrics`, see [Performance Insights counter metrics](USER_PerfInsights_Counters.md).
The following calculations are supported for the metrics:
+ Average – The average value for the metric over a period of time. Append `.avg` to the metric name.
+ Minimum – The minimum value for the metric over a period of time. Append `.min` to the metric name.
+ Maximum – The maximum value for the metric over a period of time. Append `.max` to the metric name.
+ Sum – The sum of the metric values over a period of time. Append `.sum` to the metric name.
+ Sample count – The number of times the metric was collected over a period of time. Append `.sample_count` to the metric name.
For example, assume that a metric is collected for 300 seconds (5 minutes), and that the metric is collected one time each minute. The values for each minute are 1, 2, 3, 4, and 5. In this case, the following calculations are returned:
+ Average – 3
+ Minimum – 1
+ Maximum – 5
+ Sum – 15
+ Sample count – 5
For information about using the `get-resource-metrics` AWS CLI command, see [https://docs.aws.amazon.com/cli/latest/reference/pi/get-resource-metrics.html](https://docs.aws.amazon.com/cli/latest/reference/pi/get-resource-metrics.html).
For the `--metric-queries` option, specify one or more queries that you want to get results for. Each query consists of a mandatory `Metric` and optional `GroupBy` and `Filter` parameters. The following is an example of a `--metric-queries` option specification.
```
{
"Metric": "string",
"GroupBy": {
"Group": "string",
"Dimensions": ["string", ...],
"Limit": integer
},
"Filter": {"string": "string"
...}
```
# AWS CLI examples for Performance Insights
In the following sections, learn more about the AWS Command Line Interface (AWS CLI) for Performance Insights and use AWS CLI examples.
**Topics**
+ [
## Built-in help for the AWS CLI for Performance Insights
](#USER_PerfInsights.API.CLI)
+ [
## Retrieving counter metrics
](#USER_PerfInsights.API.Examples.CounterMetrics)
+ [
## Retrieving the DB load average for top wait events
](#USER_PerfInsights.API.Examples.DBLoadAverage)
+ [
## Retrieving the DB load average for top SQL
](#USER_PerfInsights.API.Examples.DBLoadAverageTop10SQL)
+ [
## Retrieving the DB load average filtered by SQL
](#USER_PerfInsights.API.Examples.DBLoadAverageFilterBySQL)
+ [
## Retrieving the full text of a SQL statement
](#USER_PerfInsights.API.Examples.GetDimensionKeyDetails)
+ [
## Creating a performance analysis report for a time period
](#USER_PerfInsights.API.Examples.CreatePerfAnalysisReport)
+ [
## Retrieving a performance analysis report
](#USER_PerfInsights.API.Examples.GetPerfAnalysisReport)
+ [
## Listing all the performance analysis reports for the DB instance
](#USER_PerfInsights.API.Examples.ListPerfAnalysisReports)
+ [
## Deleting a performance analysis report
](#USER_PerfInsights.API.Examples.DeletePerfAnalysisReport)
+ [
## Adding tag to a performance analysis report
](#USER_PerfInsights.API.Examples.TagPerfAnalysisReport)
+ [
## Listing all the tags for a performance analysis report
](#USER_PerfInsights.API.Examples.ListTagsPerfAnalysisReport)
+ [
## Deleting tags from a performance analysis report
](#USER_PerfInsights.API.Examples.UntagPerfAnalysisReport)
## Built-in help for the AWS CLI for Performance Insights
You can view Performance Insights data using the AWS CLI. You can view help for the AWS CLI commands for Performance Insights by entering the following on the command line.
```
aws pi help
```
If you don't have the AWS CLI installed, see [Installing the AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/installing.html) in the *AWS CLI User Guide *for information about installing it.
## Retrieving counter metrics
The following screenshot shows two counter metrics charts in the AWS Management Console.
![\[Counter Metrics charts.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-api-counters-charts.png)
The following example shows how to gather the same data that the AWS Management Console uses to generate the two counter metric charts.
For Linux, macOS, or Unix:
```
aws pi get-resource-metrics \
--service-type RDS \
--identifier db-ID \
--start-time 2018-10-30T00:00:00Z \
--end-time 2018-10-30T01:00:00Z \
--period-in-seconds 60 \
--metric-queries '[{"Metric": "os.cpuUtilization.user.avg" },
{"Metric": "os.cpuUtilization.idle.avg"}]'
```
For Windows:
```
aws pi get-resource-metrics ^
--service-type RDS ^
--identifier db-ID ^
--start-time 2018-10-30T00:00:00Z ^
--end-time 2018-10-30T01:00:00Z ^
--period-in-seconds 60 ^
--metric-queries '[{"Metric": "os.cpuUtilization.user.avg" },
{"Metric": "os.cpuUtilization.idle.avg"}]'
```
You can also make a command easier to read by specifying a file for the `--metrics-query` option. The following example uses a file called query.json for the option. The file has the following contents.
```
[
{
"Metric": "os.cpuUtilization.user.avg"
},
{
"Metric": "os.cpuUtilization.idle.avg"
}
]
```
Run the following command to use the file.
For Linux, macOS, or Unix:
```
aws pi get-resource-metrics \
--service-type RDS \
--identifier db-ID \
--start-time 2018-10-30T00:00:00Z \
--end-time 2018-10-30T01:00:00Z \
--period-in-seconds 60 \
--metric-queries file://query.json
```
For Windows:
```
aws pi get-resource-metrics ^
--service-type RDS ^
--identifier db-ID ^
--start-time 2018-10-30T00:00:00Z ^
--end-time 2018-10-30T01:00:00Z ^
--period-in-seconds 60 ^
--metric-queries file://query.json
```
The preceding example specifies the following values for the options:
+ `--service-type` – `RDS` for Amazon RDS
+ `--identifier` – The resource ID for the DB instance
+ `--start-time` and `--end-time` – The ISO 8601 `DateTime` values for the period to query, with multiple supported formats
It queries for a one-hour time range:
+ `--period-in-seconds` – `60` for a per-minute query
+ `--metric-queries` – An array of two queries, each just for one metric.
The metric name uses dots to classify the metric in a useful category, with the final element being a function. In the example, the function is `avg` for each query. As with Amazon CloudWatch, the supported functions are `min`, `max`, `total`, and `avg`.
The response looks similar to the following.
```
{
"Identifier": "db-XXX",
"AlignedStartTime": 1540857600.0,
"AlignedEndTime": 1540861200.0,
"MetricList": [
{ //A list of key/datapoints
"Key": {
"Metric": "os.cpuUtilization.user.avg" //Metric1
},
"DataPoints": [
//Each list of datapoints has the same timestamps and same number of items
{
"Timestamp": 1540857660.0, //Minute1
"Value": 4.0
},
{
"Timestamp": 1540857720.0, //Minute2
"Value": 4.0
},
{
"Timestamp": 1540857780.0, //Minute 3
"Value": 10.0
}
//... 60 datapoints for the os.cpuUtilization.user.avg metric
]
},
{
"Key": {
"Metric": "os.cpuUtilization.idle.avg" //Metric2
},
"DataPoints": [
{
"Timestamp": 1540857660.0, //Minute1
"Value": 12.0
},
{
"Timestamp": 1540857720.0, //Minute2
"Value": 13.5
},
//... 60 datapoints for the os.cpuUtilization.idle.avg metric
]
}
] //end of MetricList
} //end of response
```
The response has an `Identifier`, `AlignedStartTime`, and `AlignedEndTime`. B the `--period-in-seconds` value was `60`, the start and end times have been aligned to the minute. If the `--period-in-seconds` was `3600`, the start and end times would have been aligned to the hour.
The `MetricList` in the response has a number of entries, each with a `Key` and a `DataPoints` entry. Each `DataPoint` has a `Timestamp` and a `Value`. Each `Datapoints` list has 60 data points because the queries are for per-minute data over an hour, with `Timestamp1/Minute1`, `Timestamp2/Minute2`, and so on, up to `Timestamp60/Minute60`.
Because the query is for two different counter metrics, there are two elements in the response `MetricList`.
## Retrieving the DB load average for top wait events
The following example is the same query that the AWS Management Console uses to generate a stacked area line graph. This example retrieves the `db.load.avg` for the last hour with load divided according to the top seven wait events. The command is the same as the command in [Retrieving counter metrics](#USER_PerfInsights.API.Examples.CounterMetrics). However, the query.json file has the following contents.
```
[
{
"Metric": "db.load.avg",
"GroupBy": { "Group": "db.wait_event", "Limit": 7 }
}
]
```
Run the following command.
For Linux, macOS, or Unix:
```
aws pi get-resource-metrics \
--service-type RDS \
--identifier db-ID \
--start-time 2018-10-30T00:00:00Z \
--end-time 2018-10-30T01:00:00Z \
--period-in-seconds 60 \
--metric-queries file://query.json
```
For Windows:
```
aws pi get-resource-metrics ^
--service-type RDS ^
--identifier db-ID ^
--start-time 2018-10-30T00:00:00Z ^
--end-time 2018-10-30T01:00:00Z ^
--period-in-seconds 60 ^
--metric-queries file://query.json
```
The example specifies the metric of `db.load.avg` and a `GroupBy` of the top seven wait events. For details about valid values for this example, see [DimensionGroup](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DimensionGroup.html) in the *Performance Insights API Reference.*
The response looks similar to the following.
```
{
"Identifier": "db-XXX",
"AlignedStartTime": 1540857600.0,
"AlignedEndTime": 1540861200.0,
"MetricList": [
{ //A list of key/datapoints
"Key": {
//A Metric with no dimensions. This is the total db.load.avg
"Metric": "db.load.avg"
},
"DataPoints": [
//Each list of datapoints has the same timestamps and same number of items
{
"Timestamp": 1540857660.0, //Minute1
"Value": 0.5166666666666667
},
{
"Timestamp": 1540857720.0, //Minute2
"Value": 0.38333333333333336
},
{
"Timestamp": 1540857780.0, //Minute 3
"Value": 0.26666666666666666
}
//... 60 datapoints for the total db.load.avg key
]
},
{
"Key": {
//Another key. This is db.load.avg broken down by CPU
"Metric": "db.load.avg",
"Dimensions": {
"db.wait_event.name": "CPU",
"db.wait_event.type": "CPU"
}
},
"DataPoints": [
{
"Timestamp": 1540857660.0, //Minute1
"Value": 0.35
},
{
"Timestamp": 1540857720.0, //Minute2
"Value": 0.15
},
//... 60 datapoints for the CPU key
]
},
//... In total we have 8 key/datapoints entries, 1) total, 2-8) Top Wait Events
] //end of MetricList
} //end of response
```
In this response, there are eight entries in the `MetricList`. There is one entry for the total `db.load.avg`, and seven entries each for the `db.load.avg` divided according to one of the top seven wait events. Unlike in the first example, because there was a grouping dimension, there must be one key for each grouping of the metric. There can't be only one key for each metric, as in the basic counter metric use case.
## Retrieving the DB load average for top SQL
The following example groups `db.wait_events` by the top 10 SQL statements. There are two different groups for SQL statements:
+ `db.sql` – The full SQL statement, such as `select * from customers where customer_id = 123`
+ `db.sql_tokenized` – The tokenized SQL statement, such as `select * from customers where customer_id = ?`
When analyzing database performance, it can be useful to consider SQL statements that only differ by their parameters as one logic item. So, you can use `db.sql_tokenized` when querying. However, especially when you're interested in explain plans, sometimes it's more useful to examine full SQL statements with parameters, and query grouping by `db.sql`. There is a parent-child relationship between tokenized and full SQL, with multiple full SQL (children) grouped under the same tokenized SQL (parent).
The command in this example is the similar to the command in [Retrieving the DB load average for top wait events](#USER_PerfInsights.API.Examples.DBLoadAverage). However, the query.json file has the following contents.
```
[
{
"Metric": "db.load.avg",
"GroupBy": { "Group": "db.sql_tokenized", "Limit": 10 }
}
]
```
The following example uses `db.sql_tokenized`.
For Linux, macOS, or Unix:
```
aws pi get-resource-metrics \
--service-type RDS \
--identifier db-ID \
--start-time 2018-10-29T00:00:00Z \
--end-time 2018-10-30T00:00:00Z \
--period-in-seconds 3600 \
--metric-queries file://query.json
```
For Windows:
```
aws pi get-resource-metrics ^
--service-type RDS ^
--identifier db-ID ^
--start-time 2018-10-29T00:00:00Z ^
--end-time 2018-10-30T00:00:00Z ^
--period-in-seconds 3600 ^
--metric-queries file://query.json
```
This example queries over 24 hours, with a one hour period-in-seconds.
The example specifies the metric of `db.load.avg` and a `GroupBy` of the top seven wait events. For details about valid values for this example, see [DimensionGroup](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_DimensionGroup.html) in the *Performance Insights API Reference.*
The response looks similar to the following.
```
{
"AlignedStartTime": 1540771200.0,
"AlignedEndTime": 1540857600.0,
"Identifier": "db-XXX",
"MetricList": [ //11 entries in the MetricList
{
"Key": { //First key is total
"Metric": "db.load.avg"
}
"DataPoints": [ //Each DataPoints list has 24 per-hour Timestamps and a value
{
"Value": 1.6964980544747081,
"Timestamp": 1540774800.0
},
//... 24 datapoints
]
},
{
"Key": { //Next key is the top tokenized SQL
"Dimensions": {
"db.sql_tokenized.statement": "INSERT INTO authors (id,name,email) VALUES\n( nextval(?) ,?,?)",
"db.sql_tokenized.db_id": "pi-2372568224",
"db.sql_tokenized.id": "AKIAIOSFODNN7EXAMPLE"
},
"Metric": "db.load.avg"
},
"DataPoints": [ //... 24 datapoints
]
},
// In total 11 entries, 10 Keys of top tokenized SQL, 1 total key
] //End of MetricList
} //End of response
```
This response has 11 entries in the `MetricList` (1 total, 10 top tokenized SQL), with each entry having 24 per-hour `DataPoints`.
For tokenized SQL, there are three entries in each dimensions list:
+ `db.sql_tokenized.statement` – The tokenized SQL statement.
+ `db.sql_tokenized.db_id ` – Either the native database ID used to refer to the SQL, or a synthetic ID that Performance Insights generates for you if the native database ID isn't available. This example returns the `pi-2372568224` synthetic ID.
+ `db.sql_tokenized.id` – The ID of the query inside Performance Insights.
In the AWS Management Console, this ID is called the Support ID. It's named this because the ID is data that AWS Support can examine to help you troubleshoot an issue with your database. AWS takes the security and privacy of your data extremely seriously, and almost all data is stored encrypted with your AWS KMS key. Therefore, nobody inside AWS can look at this data. In the example preceding, both the `tokenized.statement` and the `tokenized.db_id` are stored encrypted. If you have an issue with your database, AWS Support can help you by referencing the Support ID.
When querying, it might be convenient to specify a `Group` in `GroupBy`. However, for finer-grained control over the data that's returned, specify the list of dimensions. For example, if all that is needed is the `db.sql_tokenized.statement`, then a `Dimensions` attribute can be added to the query.json file.
```
[
{
"Metric": "db.load.avg",
"GroupBy": {
"Group": "db.sql_tokenized",
"Dimensions":["db.sql_tokenized.statement"],
"Limit": 10
}
}
]
```
## Retrieving the DB load average filtered by SQL
![\[Filter by SQL chart.\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/perf-insights-api-filter-chart.png)
The preceding image shows that a particular query is selected, and the top average active sessions stacked area line graph is scoped to that query. Although the query is still for the top seven overall wait events, the value of the response is filtered. The filter causes it to take into account only sessions that are a match for the particular filter.
The corresponding API query in this example is similar to the command in [Retrieving the DB load average for top SQL](#USER_PerfInsights.API.Examples.DBLoadAverageTop10SQL). However, the query.json file has the following contents.
```
[
{
"Metric": "db.load.avg",
"GroupBy": { "Group": "db.wait_event", "Limit": 5 },
"Filter": { "db.sql_tokenized.id": "AKIAIOSFODNN7EXAMPLE" }
}
]
```
For Linux, macOS, or Unix:
```
aws pi get-resource-metrics \
--service-type RDS \
--identifier db-ID \
--start-time 2018-10-30T00:00:00Z \
--end-time 2018-10-30T01:00:00Z \
--period-in-seconds 60 \
--metric-queries file://query.json
```
For Windows:
```
aws pi get-resource-metrics ^
--service-type RDS ^
--identifier db-ID ^
--start-time 2018-10-30T00:00:00Z ^
--end-time 2018-10-30T01:00:00Z ^
--period-in-seconds 60 ^
--metric-queries file://query.json
```
The response looks similar to the following.
```
{
"Identifier": "db-XXX",
"AlignedStartTime": 1556215200.0,
"MetricList": [
{
"Key": {
"Metric": "db.load.avg"
},
"DataPoints": [
{
"Timestamp": 1556218800.0,
"Value": 1.4878117913832196
},
{
"Timestamp": 1556222400.0,
"Value": 1.192823803967328
}
]
},
{
"Key": {
"Metric": "db.load.avg",
"Dimensions": {
"db.wait_event.type": "io",
"db.wait_event.name": "wait/io/aurora_redo_log_flush"
}
},
"DataPoints": [
{
"Timestamp": 1556218800.0,
"Value": 1.1360544217687074
},
{
"Timestamp": 1556222400.0,
"Value": 1.058051341890315
}
]
},
{
"Key": {
"Metric": "db.load.avg",
"Dimensions": {
"db.wait_event.type": "io",
"db.wait_event.name": "wait/io/table/sql/handler"
}
},
"DataPoints": [
{
"Timestamp": 1556218800.0,
"Value": 0.16241496598639457
},
{
"Timestamp": 1556222400.0,
"Value": 0.05163360560093349
}
]
},
{
"Key": {
"Metric": "db.load.avg",
"Dimensions": {
"db.wait_event.type": "synch",
"db.wait_event.name": "wait/synch/mutex/innodb/aurora_lock_thread_slot_futex"
}
},
"DataPoints": [
{
"Timestamp": 1556218800.0,
"Value": 0.11479591836734694
},
{
"Timestamp": 1556222400.0,
"Value": 0.013127187864644107
}
]
},
{
"Key": {
"Metric": "db.load.avg",
"Dimensions": {
"db.wait_event.type": "CPU",
"db.wait_event.name": "CPU"
}
},
"DataPoints": [
{
"Timestamp": 1556218800.0,
"Value": 0.05215419501133787
},
{
"Timestamp": 1556222400.0,
"Value": 0.05805134189031505
}
]
},
{
"Key": {
"Metric": "db.load.avg",
"Dimensions": {
"db.wait_event.type": "synch",
"db.wait_event.name": "wait/synch/mutex/innodb/lock_wait_mutex"
}
},
"DataPoints": [
{
"Timestamp": 1556218800.0,
"Value": 0.017573696145124718
},
{
"Timestamp": 1556222400.0,
"Value": 0.002333722287047841
}
]
}
],
"AlignedEndTime": 1556222400.0
} //end of response
```
In this response, all values are filtered according to the contribution of tokenized SQL AKIAIOSFODNN7EXAMPLE specified in the query.json file. The keys also might follow a different order than a query without a filter, because it's the top five wait events that affected the filtered SQL.
## Retrieving the full text of a SQL statement
The following example retrieves the full text of a SQL statement for DB instance `db-10BCD2EFGHIJ3KL4M5NO6PQRS5`. The `--group` is `db.sql`, and the `--group-identifier` is `db.sql.id`. In this example, *my-sql-id* represents a SQL ID retrieved by invoking `pi get-resource-metrics` or `pi describe-dimension-keys`.
Run the following command.
For Linux, macOS, or Unix:
```
aws pi get-dimension-key-details \
--service-type RDS \
--identifier db-10BCD2EFGHIJ3KL4M5NO6PQRS5 \
--group db.sql \
--group-identifier my-sql-id \
--requested-dimensions statement
```
For Windows:
```
aws pi get-dimension-key-details ^
--service-type RDS ^
--identifier db-10BCD2EFGHIJ3KL4M5NO6PQRS5 ^
--group db.sql ^
--group-identifier my-sql-id ^
--requested-dimensions statement
```
In this example, the dimensions details are available. Thus, Performance Insights retrieves the full text of the SQL statement, without truncating it.
```
{
"Dimensions":[
{
"Value": "SELECT e.last_name, d.department_name FROM employees e, departments d WHERE e.department_id=d.department_id",
"Dimension": "db.sql.statement",
"Status": "AVAILABLE"
},
...
]
}
```
## Creating a performance analysis report for a time period
The following example creates a performance analysis report with the `1682969503` start time and `1682979503` end time for the `db-loadtest-0` database.
```
aws pi create-performance-analysis-report \
--service-type RDS \
--identifier db-loadtest-0 \
--start-time 1682969503 \
--end-time 1682979503 \
--region us-west-2
```
The response is the unique identifier `report-0234d3ed98e28fb17` for the report.
```
{
"AnalysisReportId": "report-0234d3ed98e28fb17"
}
```
## Retrieving a performance analysis report
The following example retrieves the analysis report details for the `report-0d99cc91c4422ee61` report.
```
aws pi get-performance-analysis-report \
--service-type RDS \
--identifier db-loadtest-0 \
--analysis-report-id report-0d99cc91c4422ee61 \
--region us-west-2
```
The response provides the report status, ID, time details, and insights.
```
{
"AnalysisReport": {
"Status": "Succeeded",
"ServiceType": "RDS",
"Identifier": "db-loadtest-0",
"StartTime": 1680583486.584,
"AnalysisReportId": "report-0d99cc91c4422ee61",
"EndTime": 1680587086.584,
"CreateTime": 1680587087.139,
"Insights": [
... (Condensed for space)
]
}
}
```
## Listing all the performance analysis reports for the DB instance
The following example lists all the available performance analysis reports for the `db-loadtest-0` database.
```
aws pi list-performance-analysis-reports \
--service-type RDS \
--identifier db-loadtest-0 \
--region us-west-2
```
The response lists all the reports with the report ID, status, and time period details.
```
{
"AnalysisReports": [
{
"Status": "Succeeded",
"EndTime": 1680587086.584,
"CreationTime": 1680587087.139,
"StartTime": 1680583486.584,
"AnalysisReportId": "report-0d99cc91c4422ee61"
},
{
"Status": "Succeeded",
"EndTime": 1681491137.914,
"CreationTime": 1681491145.973,
"StartTime": 1681487537.914,
"AnalysisReportId": "report-002633115cc002233"
},
{
"Status": "Succeeded",
"EndTime": 1681493499.849,
"CreationTime": 1681493507.762,
"StartTime": 1681489899.849,
"AnalysisReportId": "report-043b1e006b47246f9"
},
{
"Status": "InProgress",
"EndTime": 1682979503.0,
"CreationTime": 1682979618.994,
"StartTime": 1682969503.0,
"AnalysisReportId": "report-01ad15f9b88bcbd56"
}
]
}
```
## Deleting a performance analysis report
The following example deletes the analysis report for the `db-loadtest-0` database.
```
aws pi delete-performance-analysis-report \
--service-type RDS \
--identifier db-loadtest-0 \
--analysis-report-id report-0d99cc91c4422ee61 \
--region us-west-2
```
## Adding tag to a performance analysis report
The following example adds a tag with a key `name` and value `test-tag` to the `report-01ad15f9b88bcbd56` report.
```
aws pi tag-resource \
--service-type RDS \
--resource-arn arn:aws:pi:us-west-2:356798100956:perf-reports/RDS/db-loadtest-0/report-01ad15f9b88bcbd56 \
--tags Key=name,Value=test-tag \
--region us-west-2
```
## Listing all the tags for a performance analysis report
The following example lists all the tags for the `report-01ad15f9b88bcbd56` report.
```
aws pi list-tags-for-resource \
--service-type RDS \
--resource-arn arn:aws:pi:us-west-2:356798100956:perf-reports/RDS/db-loadtest-0/report-01ad15f9b88bcbd56 \
--region us-west-2
```
The response lists the value and key for all the tags added to the report:
```
{
"Tags": [
{
"Value": "test-tag",
"Key": "name"
}
]
}
```
## Deleting tags from a performance analysis report
The following example deletes the `name` tag from the `report-01ad15f9b88bcbd56` report.
```
aws pi untag-resource \
--service-type RDS \
--resource-arn arn:aws:pi:us-west-2:356798100956:perf-reports/RDS/db-loadtest-0/report-01ad15f9b88bcbd56 \
--tag-keys name \
--region us-west-2
```
After the tag is deleted, calling the `list-tags-for-resource` API doesn't list this tag.
# Logging Performance Insights calls using AWS CloudTrail
Performance Insights runs with AWS CloudTrail, a service that provides a record of actions taken by a user, role, or an AWS service in Performance Insights. CloudTrail captures all API calls for Performance Insights as events. This capture includes calls from the Amazon RDS console and from code calls to the Performance Insights API operations.
If you create a trail, you can enable continuous delivery of CloudTrail events to an Amazon S3 bucket, including events for Performance Insights. If you don't configure a trail, you can still view the most recent events in the CloudTrail console in **Event history**. Using the data collected by CloudTrail, you can determine certain information. This information includes the request that was made to Performance Insights, the IP address the request was made from, who made the request, and when it was made. It also includes additional details.
To learn more about CloudTrail, see the [AWS CloudTrail User Guide](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/).
## Working with Performance Insights information in CloudTrail
CloudTrail is enabled on your AWS account when you create the account. When activity occurs in Performance Insights, that activity is recorded in a CloudTrail event along with other AWS service events in the CloudTrail console in **Event history**. You can view, search, and download recent events in your AWS account. For more information, see [Viewing Events with CloudTrail Event History](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/view-cloudtrail-events.html) in *AWS CloudTrail User Guide.*
For an ongoing record of events in your AWS account, including events for Performance Insights, create a trail. A *trail* enables CloudTrail to deliver log files to an Amazon S3 bucket. By default, when you create a trail in the console, the trail applies to all AWS Regions. The trail logs events from all AWS Regions in the AWS partition and delivers the log files to the Amazon S3 bucket that you specify. Additionally, you can configure other AWS services to further analyze and act upon the event data collected in CloudTrail logs. For more information, see the following topics in *AWS CloudTrail User Guide:*
+ [Overview for Creating a Trail](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-create-and-update-a-trail.html)
+ [CloudTrail Supported Services and Integrations](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-aws-service-specific-topics.html#cloudtrail-aws-service-specific-topics-integrations)
+ [Configuring Amazon SNS Notifications for CloudTrail](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/getting_notifications_top_level.html)
+ [Receiving CloudTrail Log Files from Multiple Regions](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/receive-cloudtrail-log-files-from-multiple-regions.html) and [Receiving CloudTrail Log Files from Multiple Accounts](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-receive-logs-from-multiple-accounts.html)
All Performance Insights operations are logged by CloudTrail and are documented in the [Performance Insights API Reference](https://docs.aws.amazon.com/performance-insights/latest/APIReference/Welcome.html). For example, calls to the `DescribeDimensionKeys` and `GetResourceMetrics` operations generate entries in the CloudTrail log files.
Every event or log entry contains information about who generated the request. The identity information helps you determine the following:
+ Whether the request was made with root or IAM user credentials.
+ Whether the request was made with temporary security credentials for a role or federated user.
+ Whether the request was made by another AWS service.
For more information, see the [CloudTrail userIdentity Element](https://docs.aws.amazon.com/awscloudtrail/latest/userguide/cloudtrail-event-reference-user-identity.html).
## Performance Insights log file entries
A *trail* is a configuration that enables delivery of events as log files to an Amazon S3 bucket that you specify. CloudTrail log files contain one or more log entries. An *event* represents a single request from any source. Each event includes information about the requested operation, the date and time of the operation, request parameters, and so on. CloudTrail log files aren't an ordered stack trace of the public API calls, so they don't appear in any specific order.
The following example shows a CloudTrail log entry that demonstrates the `GetResourceMetrics` operation.
```
{
"eventVersion": "1.05",
"userIdentity": {
"type": "IAMUser",
"principalId": "AKIAIOSFODNN7EXAMPLE",
"arn": "arn:aws:iam::123456789012:user/johndoe",
"accountId": "123456789012",
"accessKeyId": "AKIAI44QH8DHBEXAMPLE",
"userName": "johndoe"
},
"eventTime": "2019-12-18T19:28:46Z",
"eventSource": "pi.amazonaws.com",
"eventName": "GetResourceMetrics",
"awsRegion": "us-east-1",
"sourceIPAddress": "72.21.198.67",
"userAgent": "aws-cli/1.16.240 Python/3.7.4 Darwin/18.7.0 botocore/1.12.230",
"requestParameters": {
"identifier": "db-YTDU5J5V66X7CXSCVDFD2V3SZM",
"metricQueries": [
{
"metric": "os.cpuUtilization.user.avg"
},
{
"metric": "os.cpuUtilization.idle.avg"
}
],
"startTime": "Dec 18, 2019 5:28:46 PM",
"periodInSeconds": 60,
"endTime": "Dec 18, 2019 7:28:46 PM",
"serviceType": "RDS"
},
"responseElements": null,
"requestID": "9ffbe15c-96b5-4fe6-bed9-9fccff1a0525",
"eventID": "08908de0-2431-4e2e-ba7b-f5424f908433",
"eventType": "AwsApiCall",
"recipientAccountId": "123456789012"
}
```
# Performance Insights API and interface VPC endpoints (AWS PrivateLink)
You can use AWS PrivateLink to create a private connection between your VPC and Amazon RDS Performance Insights. You can access Performance Insights as if it were in your VPC, without the use of an internet gateway, NAT device, VPN connection, or Direct Connect connection. Instances in your VPC don't need public IP addresses to access Performance Insights.
You establish this private connection by creating an *interface endpoint*, powered by AWS PrivateLink. We create an endpoint network interface in each subnet that you enable for the interface endpoint. These are requester-managed network interfaces that serve as the entry point for traffic destined for Performance Insights.
For more information, see [Access AWS services through AWS PrivateLink](https://docs.aws.amazon.com/vpc/latest/privatelink/privatelink-access-aws-services.html) in the *AWS PrivateLink Guide*.
## Considerations for Performance Insights
Before you set up an interface endpoint for Performance Insights, review [Considerations](https://docs.aws.amazon.com/vpc/latest/privatelink/create-interface-endpoint.html#considerations-interface-endpoints) in the *AWS PrivateLink Guide*.
Performance Insights supports making calls to all of its API actions through the interface endpoint.
By default, full access to Performance Insights is allowed through the interface endpoint. To control traffic to Performance Insights through the interface endpoint, associate a security group with the endpoint network interfaces.
## Availability
Performance Insights API currently supports VPC endpoints in AWS Regions that support Performance Insights. For information about Performance Insights availability, see [Supported Regions and DB engines for Performance Insights in Amazon RDS](Concepts.RDS_Fea_Regions_DB-eng.Feature.PerformanceInsights.md) .
## Create an interface endpoint for Performance Insights
You can create an interface endpoint for Performance Insights using either the Amazon VPC console or the AWS Command Line Interface (AWS CLI). For more information, see [Create an interface endpoint](https://docs.aws.amazon.com/vpc/latest/privatelink/create-interface-endpoint.html#create-interface-endpoint-aws) in the *AWS PrivateLink Guide*.
Create an interface endpoint for Performance Insights using the following service name:
If you enable private DNS for the interface endpoint, you can make API requests to Performance Insights using its default Regional DNS name. For example, `pi.us-east-1.amazonaws.com`.
## Creating a VPC endpoint policy for Performance Insights API
An endpoint policy is an IAM resource that you can attach to an interface endpoint. The default endpoint policy allows full access to Performance Insights through the interface endpoint. To control the access allowed to Performance Insights from your VPC, attach a custom endpoint policy to the interface endpoint.
An endpoint policy specifies the following information:
+ The principals that can perform actions (AWS accounts, IAM users, and IAM roles).
+ The actions that can be performed.
+ The resources on which the actions can be performed.
For more information, see [Control access to services using endpoint policies](https://docs.aws.amazon.com/vpc/latest/privatelink/vpc-endpoints-access.html) in the *AWS PrivateLink Guide*.
**Example: VPC endpoint policy for Performance Insights actions**
The following is an example of a custom endpoint policy. When you attach this policy to your interface endpoint, it grants access to the listed Performance Insights actions for all principals on all resources.
```
{
"Statement":[
{
"Principal":"*",
"Effect":"Allow",
"Action":[
"rds:CreatePerformanceAnalysisReport",
"rds:DeletePerformanceAnalysisReport",
"rds:GetPerformanceAnalysisReport"
],
"Resource":"*"
}
]
}
```
**Example: VPC endpoint policy that denies all access from a specified AWS account**
The following VPC endpoint policy denies AWS account `123456789012` all access to resources using the endpoint. The policy allows all actions from other accounts.
```
{
"Statement": [
{
"Action": "*",
"Effect": "Allow",
"Resource": "*",
"Principal": "*"
},
{
"Action": "*",
"Effect": "Deny",
"Resource": "*",
"Principal": { "AWS": [ "123456789012" ] }
}
]
}
```
## IP addressing for Performance Insights
IP addresses enable resources in your VPC to communicate with each other, and with resources over the internet. Performance Insights supports both IPv4 and IPv6 addressing protocols. By default, Performance Insights and Amazon VPC use the IPv4 addressing protocol. You can't turn off this behavior. When you create a VPC, make sure to specify an IPv4 CIDR block (a range of private IPv4 addresses).
You can optionally assign an IPv6 CIDR block to your VPC and subnets, and assign IPv6 addresses from that block to RDS resources in your subnet. Support for the IPv6 protocol expands the number of supported IP addresses. By using the IPv6 protocol, you ensure that you have sufficient available addresses for the future growth of the internet. New and existing RDS resources can use IPv4 and IPv6 addresses within your VPC. Configuring, securing, and translating network traffic between the two protocols used in different parts of an application can cause operational overhead. You can standardize on the IPv6 protocol for Amazon RDS resources to simplify your network configuration. For more information about service endpoints and quotas, see [Amazon Relational Database Service endpoints and quotas](https://docs.aws.amazon.com/general/latest/gr/rds-service.html).
For more information about Amazon RDS IP addressing, see [Amazon RDS IP addressing](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_VPC.WorkingWithRDSInstanceinaVPC.html#USER_VPC.IP_addressing).
# Analyzing performance anomalies with Amazon DevOps Guru for Amazon RDS
Amazon DevOps Guru is a fully managed operations service that helps developers and operators improve the performance and availability of their applications. DevOps Guru offloads the tasks associated with identifying operational issues so that you can quickly implement recommendations to improve your application. For more information, see [What is Amazon DevOps Guru?](https://docs.aws.amazon.com/devops-guru/latest/userguide/welcome.html) in the *Amazon DevOps Guru User Guide*.
DevOps Guru detects, analyzes, and makes recommendations for existing operational issues for all Amazon RDS DB engines. DevOps Guru for RDS extends this capability by applying machine learning to Performance Insights metrics for RDS for PostgreSQL databases. These monitoring features allow DevOps Guru for RDS to detect and diagnose performance bottlenecks and recommend specific corrective actions. DevOps Guru for RDS can also detect problematic conditions in your RDS for PostgreSQL database before they occur.
You can now view these recommendations in RDS console. For more information, see [Recommendations from Amazon RDS](monitoring-recommendations.md).
The following video is an overview of DevOps Guru for RDS.
[](http://www.youtube.com/watch?v=N3NNYgzYUDA)
For a deep dive on this subject, see [Amazon DevOps Guru for RDS under the hood.](https://aws.amazon.com/blogs/database/amazon-devops-guru-for-rds-under-the-hood/)
**Topics**
+ [
## Benefits of DevOps Guru for RDS
](#devops-guru-for-rds.benefits)
+ [
## How DevOps Guru for RDS works
](#devops-guru-for-rds.how-it-works)
+ [
## Setting up DevOps Guru for RDS
](#devops-guru-for-rds.configuring)
## Benefits of DevOps Guru for RDS
If you're responsible for RDS for PostgreSQL database, you might not know that an event or regression that is affecting that database is occurring. When you learn about the issue, you might not know why it's occurring or what to do about it. Rather than turning to a database administrator (DBA) for help or relying on third-party tools, you can follow recommendations from DevOps Guru for RDS.
You gain the following advantages from the detailed analysis of DevOps Guru for RDS:
**Fast diagnosis**
DevOps Guru for RDS continuously monitors and analyzes database telemetry. Performance Insights, Enhanced Monitoring, and Amazon CloudWatch collect telemetry data for your database instance. DevOps Guru for RDS uses statistical and machine learning techniques to mine this data and detect anomalies. To learn more about telemetry data, see [Monitoring DB load with Performance Insights on Amazon RDS](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.html) and [Monitoring OS metrics with Enhanced Monitoring](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_Monitoring.OS.html) in the *Amazon RDS User Guide*.
**Fast resolution**
Each anomaly identifies the performance issue and suggests avenues of investigation or corrective actions. For example, DevOps Guru for RDS might recommend that you investigate specific wait events. Or it might recommend that you tune your application pool settings to limit the number of database connections. Based on these recommendations, you can resolve performance issues more quickly than by troubleshooting manually.
**Proactive insights**
DevOps Guru for RDS uses metrics from your resources to detect potentially problematic behavior before it becomes a bigger problem. For example, it can detect when your database is using an increasing number of on-disk temporary tables, which could start to impact performance. DevOps Guru then provides recommendations to help you address issues before they become bigger problems.
**Deep knowledge of Amazon engineers and machine learning**
To detect performance issues and help you resolve bottlenecks, DevOps Guru for RDS relies on machine learning (ML) and advanced mathematical formulas. Amazon database engineers contributed to the development of the DevOps Guru for RDS findings, which encapsulate many years of managing hundreds of thousands of databases. By drawing on this collective knowledge, DevOps Guru for RDS can teach you best practices.
## How DevOps Guru for RDS works
DevOps Guru for RDS collects data about your RDS for PostgreSQL databases from Amazon RDS Performance Insights. The most important metric is `DBLoad`. DevOps Guru for RDS consumes the Performance Insights metrics, analyzes them with machine learning, and publishes insights to the dashboard.
An *insight* is a collection of related anomalies that were detected by DevOps Guru.
In DevOps Guru for RDS, an *anomaly* is a pattern that deviates from what is considered normal performance for your RDS for PostgreSQL database.
### Proactive insights
A *proactive insight* lets you know about problematic behavior before it occurs. It contains anomalies with recommendations and related metrics to help you address issues in your RDS for PostgreSQL databases before become bigger problems. These insights are published in the DevOps Guru dashboard.
For example, DevOps Guru might detect that your RDS for PostgreSQL database is creating many on-disk temporary tables. If not addressed, this trend might lead to performance issues. Each proactive insight includes recommendations for corrective behavior and links to relevant topics in [Tuning RDS for PostgreSQL with Amazon DevOps Guru proactive insights](PostgreSQL.Tuning_proactive_insights.md). For more information, see [Working with insights in DevOps Guru](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-insights.html) in the *Amazon DevOps Guru User Guide*.
### Reactive insights
A *reactive insight* identifies anomalous behavior as it occurs. If DevOps Guru for RDS finds performance issues in your RDS for PostgreSQL DB instances, it publishes a reactive insight in the DevOps Guru dashboard. For more information, see [Working with insights in DevOps Guru](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-insights.html) in the *Amazon DevOps Guru User Guide*.
#### Causal anomalies
A *causal anomaly* is a top-level anomaly within a reactive insight. **Database load (DB load)** is the causal anomaly for DevOps Guru for RDS.
An anomaly measures performance impact by assigning a severity level of **High**, **Medium**, or **Low**. To learn more, see [Key concepts for DevOps Guru for RDS](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-rds.overview.definitions.html) in the *Amazon DevOps Guru User Guide*.
If DevOps Guru detects a current anomaly on your DB instance, you're alerted in the **Databases** page of the RDS console. The console also alerts you to anomalies that occurred in the past 24 hours. To go to the anomaly page from the RDS console, choose the link in the alert message. The RDS console also alerts you in the page for your RDS for PostgreSQL DB instance.
#### Contextual anomalies
A *contextual anomaly* is a finding within **Database load (DB load)** that is related to a reactive insight. Each contextual anomaly describes a specific RDS for PostgreSQL performance issue that requires investigation. For example, DevOps Guru for RDS might recommend that you consider increasing CPU capacity or investigate wait events that are contributing to DB load.
**Important**
We recommend that you test any changes on a test instance before modifying a production instance. In this way, you understand the impact of the change.
To learn more, see [Analyzing anomalies in Amazon RDS](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-rds.analyzing.html) in the *Amazon DevOps Guru User Guide*.
## Setting up DevOps Guru for RDS
To allow DevOps Guru for Amazon RDS to publish insights for a RDS for PostgreSQL database, complete the following tasks.
**Topics**
+ [
### Configuring IAM access policies for DevOps Guru for RDS
](#devops-guru-for-rds.configuring.access)
+ [
### Turning on Performance Insights for your RDS for PostgreSQL DB instances
](#devops-guru-for-rds.configuring.performance-insights)
+ [
### Turning on DevOps Guru and specifying resource coverage
](#devops-guru-for-rds.configuring.coverage)
### Configuring IAM access policies for DevOps Guru for RDS
To view alerts from DevOps Guru in the RDS console, your AWS Identity and Access Management (IAM) user or role must have either of the following policies:
+ The AWS managed policy `AmazonDevOpsGuruConsoleFullAccess`
+ The AWS managed policy `AmazonDevOpsGuruConsoleReadOnlyAccess` and either of the following policies:
+ The AWS managed policy `AmazonRDSFullAccess`
+ A customer managed policy that includes `pi:GetResourceMetrics` and `pi:DescribeDimensionKeys`
For more information, see [Configuring access policies for Performance Insights](USER_PerfInsights.access-control.md).
### Turning on Performance Insights for your RDS for PostgreSQL DB instances
DevOps Guru for RDS relies on Performance Insights for its data. Without Performance Insights, DevOps Guru publishes anomalies, but doesn't include the detailed analysis and recommendations.
When you create or modify a RDS for PostgreSQL DB instance, you can turn on Performance Insights. For more information, see [Turning Performance Insights on and off for Amazon RDS](USER_PerfInsights.Enabling.md).
### Turning on DevOps Guru and specifying resource coverage
You can turn on DevOps Guru to have it monitor your RDS for PostgreSQL databases in either of the following ways.
**Topics**
+ [
#### Turning on DevOps Guru in the RDS console
](#devops-guru-for-rds.configuring.coverage.rds-console)
+ [
#### Adding RDS for PostgreSQL resources in the DevOps Guru console
](#devops-guru-for-rds.configuring.coverage.guru-console)
+ [
#### Adding RDS for PostgreSQL resources using CloudFormation
](#devops-guru-for-rds.configuring.coverage.cfn)
#### Turning on DevOps Guru in the RDS console
You can take multiple paths in the Amazon RDS console to turn on DevOps Guru.
**Topics**
+ [
##### Turning on DevOps Guru when you create an RDS for PostgreSQL database
](#devops-guru-for-rds.configuring.coverage.rds-console.create)
+ [
##### Turning on DevOps Guru from the notification banner
](#devops-guru-for-rds.configuring.coverage.rds-console.existing)
+ [
##### Responding to a permissions error when you turn on DevOps Guru
](#devops-guru-for-rds.configuring.coverage.rds-console.error)
##### Turning on DevOps Guru when you create an RDS for PostgreSQL database
The creation workflow includes a setting that turns on DevOps Guru coverage for your database. This setting is turned on by default when you choose the **Production** template.
**To turn on DevOps Guru when you create an RDS for PostgreSQL database**
1. Sign in to the AWS Management Console and open the Amazon RDS console at [https://console.aws.amazon.com/rds/](https://console.aws.amazon.com/rds/).
1. Follow the steps in [Creating a DB instance](USER_CreateDBInstance.md#USER_CreateDBInstance.Creating), up to but not including the step where you choose monitoring settings.
1. In **Monitoring**, choose **Turn on Performance Insights**. For DevOps Guru for RDS to provide detailed analysis of performance anomalies, Performance Insights must be turned on.
1. Choose **Turn on DevOps Guru**.
![\[Turn on DevOps Guru when you create a DB instance\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/devops-guru-enable-create.png)
1. Create a tag for your database so that DevOps Guru can monitor it. Do the following:
+ In the text field for **Tag key**, enter a name that begins with **Devops-Guru-**.
+ In the text field for **Tag value**, enter any value. For example, if you enter **rds-database-1** for the name of your RDS for PostgreSQL database, you can also enter **rds-database-1** as the tag value.
For more information about tags, see "[Use tags to identify resources in your DevOps Guru applications](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-resource-tags.html)" in the *Amazon DevOps Guru User Guide*.
1. Complete the remaining steps in [Creating a DB instance](USER_CreateDBInstance.md#USER_CreateDBInstance.Creating).
##### Turning on DevOps Guru from the notification banner
If your resources aren't covered by DevOps Guru, Amazon RDS notifies you with a banner in the following locations:
+ The **Monitoring** tab of a DB cluster instance
+ The Performance Insights dashboard
![\[DevOps Guru banner\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/devops-guru-enable-banner.png)
**To turn on DevOps Guru for your RDS for PostgreSQL database**
1. In the banner, choose **Turn on DevOps Guru for RDS**.
1. Enter a tag key name and value. For more information about tags, see "[Use tags to identify resources in your DevOps Guru applications](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-resource-tags.html)" in the *Amazon DevOps Guru User Guide*.
![\[Turn on DevOps Guru in the RDS console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/devops-guru-turn-on.png)
1. Choose **Turn on DevOps Guru**.
##### Responding to a permissions error when you turn on DevOps Guru
If you turn on DevOps Guru from the RDS console when you create a database, RDS might display the following banner about missing permissions.
![\[Banner with a missing permissions error\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/devops-guru-permissions-error.png)
**To respond to a permissions error**
1. Grant your IAM user or role the user managed role `AmazonDevOpsGuruConsoleFullAccess`. For more information, see [Configuring IAM access policies for DevOps Guru for RDS](#devops-guru-for-rds.configuring.access).
1. Open the RDS console.
1. In the navigation pane, choose **Performance Insights**.
1. Choose a DB instance in the cluster that you just created.
1. Choose the switch to turn on **DevOps Guru for RDS**.
![\[Choose the switch to turn on DevOps Guru for RDS\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/devops-guru-pi-toggle-off.png)
1. Choose a tag value. For more information, see "[Use tags to identify resources in your DevOps Guru applications](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-resource-tags.html)" in the *Amazon DevOps Guru User Guide*.
![\[Turn on DevOps Guru in the Amazon RDS console\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/devops-guru-turn-on.png)
1. Choose **Turn on DevOps Guru**.
#### Adding RDS for PostgreSQL resources in the DevOps Guru console
You can specify your DevOps Guru resource coverage on the DevOps Guru console. Follow the step described in [Specify your DevOps Guru resource coverage](https://docs.aws.amazon.com/devops-guru/latest/userguide/choose-coverage.html) in the *Amazon DevOps Guru User Guide*. When you edit your analyzed resources, choose one of the following options:
+ Choose **All account resources** to analyze all supported resources, including the RDS for PostgreSQL databases, in your AWS account and Region.
+ Choose **CloudFormation stacks** to analyze the RDS for PostgreSQL databases that are in stacks you choose. For more information, see [Use AWS CloudFormation stacks to identify resources in your DevOps Guru applications](https://docs.aws.amazon.com//devops-guru/latest/userguide/working-with-cfn-stacks.html) in the *Amazon DevOps Guru User Guide*.
+ Choose **Tags** to analyze the RDS for PostgreSQL databases that you have tagged. For more information, see [Use tags to identify resources in your DevOps Guru applications](https://docs.aws.amazon.com/devops-guru/latest/userguide/working-with-resource-tags.html) in the *Amazon DevOps Guru User Guide*.
For more information, see [Enable DevOps Guru](https://docs.aws.amazon.com/devops-guru/latest/userguide/getting-started-enable-service.html) in the *Amazon DevOps Guru User Guide*.
#### Adding RDS for PostgreSQL resources using CloudFormation
You can use tags to add coverage for your RDS for PostgreSQL resources to your CloudFormation templates. The following procedure assumes that you have a CloudFormation template both for your RDS for PostgreSQL DB instance and DevOps Guru stack.
**To specify an RDS for PostgreSQL DB instance using a CloudFormation tag**
1. In the CloudFormation template for your DB instance, define a tag using a key/value pair.
The following example assigns the value `my-db-instance1` to `Devops-guru-cfn-default` for an RDS for PostgreSQL DB instance.
```
MyDBInstance1:
Type: "AWS::RDS::DBInstance"
Properties:
DBInstanceIdentifier: my-db-instance1
Tags:
- Key: Devops-guru-cfn-default
Value: devopsguru-my-db-instance1
```
1. In the CloudFormation template for your DevOps Guru stack, specify the same tag in your resource collection filter.
The following example configures DevOps Guru to provide coverage for the resource with the tag value `my-db-instance1`.
```
DevOpsGuruResourceCollection:
Type: AWS::DevOpsGuru::ResourceCollection
Properties:
ResourceCollectionFilter:
Tags:
- AppBoundaryKey: "Devops-guru-cfn-default"
TagValues:
- "devopsguru-my-db-instance1"
```
The following example provides coverage for all resources within the application boundary `Devops-guru-cfn-default`.
```
DevOpsGuruResourceCollection:
Type: AWS::DevOpsGuru::ResourceCollection
Properties:
ResourceCollectionFilter:
Tags:
- AppBoundaryKey: "Devops-guru-cfn-default"
TagValues:
- "*"
```
For more information, see [AWS::DevOpsGuru::ResourceCollection](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-devopsguru-resourcecollection.html) and [AWS::RDS::DBInstance](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-rds-dbinstance.html) in the *CloudFormation User Guide*.
# Monitoring OS metrics with Enhanced Monitoring
With Enhanced Monitoring, you can monitor the operating system of your DB instance in real time. When you want to see how different processes or threads use the CPU, Enhanced Monitoring metrics are useful.
**Topics**
+ [
## Overview of Enhanced Monitoring
](#USER_Monitoring.OS.overview)
+ [
# Setting up and enabling Enhanced Monitoring
](USER_Monitoring.OS.Enabling.md)
+ [
# Viewing OS metrics in the RDS console
](USER_Monitoring.OS.Viewing.md)
+ [
# Viewing OS metrics using CloudWatch Logs
](USER_Monitoring.OS.CloudWatchLogs.md)
## Overview of Enhanced Monitoring
Amazon RDS provides metrics in real time for the operating system (OS) that your DB instance runs on. You can view all the system metrics and process information for your RDS DB instances on the console. You can manage which metrics you want to monitor for each instance and customize the dashboard according to your requirements. For descriptions of the Enhanced Monitoring metrics, see [OS metrics in Enhanced Monitoring](USER_Monitoring-Available-OS-Metrics.md).
RDS delivers the metrics from Enhanced Monitoring into your Amazon CloudWatch Logs account. You can create metrics filters in CloudWatch from CloudWatch Logs and display the graphs on the CloudWatch dashboard. You can consume the Enhanced Monitoring JSON output from CloudWatch Logs in a monitoring system of your choice. For more information, see [Enhanced Monitoring](https://aws.amazon.com/rds/faqs/#Enhanced_Monitoring) in the Amazon RDS FAQs.
**Topics**
+ [
### Enhanced Monitoring availability
](#USER_Monitoring.OS.Availability)
+ [
### Differences between CloudWatch and Enhanced Monitoring metrics
](#USER_Monitoring.OS.CloudWatchComparison)
+ [
### Retention of Enhanced Monitoring metrics
](#USER_Monitoring.OS.retention)
+ [
### Cost of Enhanced Monitoring
](#USER_Monitoring.OS.cost)
### Enhanced Monitoring availability
Enhanced Monitoring is available for the following database engines:
+ Db2
+ MariaDB
+ Microsoft SQL Server
+ MySQL
+ Oracle
+ PostgreSQL
### Differences between CloudWatch and Enhanced Monitoring metrics
A *hypervisor* creates and runs virtual machines (VMs). Using a hypervisor, an instance can support multiple guest VMs by virtually sharing memory and CPU. CloudWatch gathers metrics about CPU utilization from the hypervisor for a DB instance. In contrast, Enhanced Monitoring gathers its metrics from an agent on the DB instance.
You might find differences between the CloudWatch and Enhanced Monitoring measurements, because the hypervisor layer performs a small amount of work. The differences can be greater if your DB instances use smaller instance classes. In this scenario, more virtual machines (VMs) are probably managed by the hypervisor layer on a single physical instance.
For descriptions of the Enhanced Monitoring metrics, see [OS metrics in Enhanced Monitoring](USER_Monitoring-Available-OS-Metrics.md). For more information about CloudWatch metrics, see the *[Amazon CloudWatch User Guide](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/working_with_metrics.html)*.
### Retention of Enhanced Monitoring metrics
By default, Enhanced Monitoring metrics are stored for 30 days in the CloudWatch Logs. This retention period is different from typical CloudWatch metrics.
To modify the amount of time the metrics are stored in the CloudWatch Logs, change the retention for the `RDSOSMetrics` log group in the CloudWatch console. For more information, see [Change log data retention in CloudWatch logs](https://docs.aws.amazon.com/AmazonCloudWatch/latest/logs/Working-with-log-groups-and-streams.html#SettingLogRetention) in the *Amazon CloudWatch Logs User Guide*.
### Cost of Enhanced Monitoring
Enhanced Monitoring metrics are stored in the CloudWatch Logs instead of in CloudWatch metrics. The cost of Enhanced Monitoring depends on the following factors:
+ You are charged for Enhanced Monitoring only if you exceed the amount of data transfer and storage provided by Amazon CloudWatch Logs. Charges are based on CloudWatch Logs data transfer and storage rates.
+ The amount of information transferred for an RDS instance is directly proportional to the defined granularity for the Enhanced Monitoring feature. A smaller monitoring interval results in more frequent reporting of OS metrics and increases your monitoring cost. To manage costs, set different granularities for different instances in your accounts.
+ Usage costs for Enhanced Monitoring are applied for each DB instance that Enhanced Monitoring is enabled for. Monitoring a large number of DB instances is more expensive than monitoring only a few.
+ DB instances that support a more compute-intensive workload have more OS process activity to report and higher costs for Enhanced Monitoring.
For more information about pricing, see [Amazon CloudWatch pricing](https://aws.amazon.com/cloudwatch/pricing/).
# Setting up and enabling Enhanced Monitoring
To use Enhanced Monitoring, you must create an IAM role, and then enable Enhanced Monitoring.
**Topics**
+ [
## Creating an IAM role for Enhanced Monitoring
](#USER_Monitoring.OS.Enabling.Prerequisites)
+ [
## Turning Enhanced Monitoring on and off
](#USER_Monitoring.OS.Enabling.Procedure)
+ [
## Protecting against the confused deputy problem
](#USER_Monitoring.OS.confused-deputy)
## Creating an IAM role for Enhanced Monitoring
Enhanced Monitoring requires permission to act on your behalf to send OS metric information to CloudWatch Logs. You grant Enhanced Monitoring permissions using an AWS Identity and Access Management (IAM) role. You can either create this role when you enable Enhanced Monitoring or create it beforehand.
**Topics**
+ [
### Creating the IAM role when you enable Enhanced Monitoring
](#USER_Monitoring.OS.Enabling.Prerequisites.creating-role-automatically)
+ [
### Creating the IAM role before you enable Enhanced Monitoring
](#USER_Monitoring.OS.Enabling.Prerequisites.creating-role-manually)
### Creating the IAM role when you enable Enhanced Monitoring
When you enable Enhanced Monitoring in the RDS console, Amazon RDS can create the required IAM role for you. The role is named `rds-monitoring-role`. RDS uses this role for the specified DB instance, read replica, or Multi-AZ DB cluster.
**To create the IAM role when enabling Enhanced Monitoring**
1. Follow the steps in [Turning Enhanced Monitoring on and off](#USER_Monitoring.OS.Enabling.Procedure).
1. Set **Monitoring Role** to **Default** in the step where you choose a role.
### Creating the IAM role before you enable Enhanced Monitoring
You can create the required role before you enable Enhanced Monitoring. When you enable Enhanced Monitoring, specify your new role's name. You must create this required role if you enable Enhanced Monitoring using the AWS CLI or the RDS API.
The user that enables Enhanced Monitoring must be granted the `PassRole` permission. For more information, see Example 2 in [Granting a user permissions to pass a role to an AWS service](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_roles_use_passrole.html) in the *IAM User Guide*.
**To create an IAM role for Amazon RDS enhanced monitoring**
1. Open the [IAM console](https://console.aws.amazon.com/iam/home?#home) at [https://console.aws.amazon.com](https://console.aws.amazon.com/).
1. In the navigation pane, choose **Roles**.
1. Choose **Create role**.
1. Choose the **AWS service** tab, and then choose **RDS** from the list of services.
1. Choose **RDS - Enhanced Monitoring**, and then choose **Next**.
1. Ensure that the **Permissions policies** shows **AmazonRDSEnhancedMonitoringRole**, and then choose **Next**.
1. For **Role name**, enter a name for your role. For example, enter **emaccess**.
The trusted entity for your role is the AWS service **monitoring.rds.amazonaws.com**.
1. Choose **Create role**.
## Turning Enhanced Monitoring on and off
You can manage Enhanced Monitoring using the AWS Management Console, AWS CLI, or RDS API. You can set different granularities for metric collection on each DB instance.
### Console
You can turn on Enhanced Monitoring when you create a DB instance, Multi-AZ DB cluster, or read replica, or when you modify a DB instance or Multi-AZ DB cluster. If you modify a DB instance to turn on Enhanced Monitoring, you don't need to reboot your DB instance for the change to take effect.
You can turn on Enhanced Monitoring in the RDS console when you do one of the following actions in the **Databases** page:
+ **Create a DB instance or Multi-AZ DB cluster** – Choose **Create database**.
+ **Create a read replica** – Choose **Actions**, then **Create read replica**.
+ **Modify a DB instance or Multi-AZ DB cluster** – Choose **Modify**.
**To turn Enhanced Monitoring on or off in the RDS console**
1. Scroll to **Additional configuration**.
1. In **Monitoring**, choose **Enable Enhanced Monitoring** for your DB instance or read replica. Deselect the option to disable Enhanced Monitoring.
1. Set the **Monitoring Role** property to the IAM role that you created to permit Amazon RDS to communicate with Amazon CloudWatch Logs for you, or choose **Default** to have RDS create a role for you named `rds-monitoring-role`.
1. Set the **Granularity** property to the interval, in seconds, between points when metrics are collected for your DB instance or read replica. The **Granularity** property can be set to one of the following values: `1`, `5`, `10`, `15`, `30`, or `60`.
The fastest that the RDS console refreshes is every 5 seconds. If you set the granularity to 1 second in the RDS console, you still see updated metrics only every 5 seconds. You can retrieve 1-second metric updates by using CloudWatch Logs.
### AWS CLI
To turn on Enhanced Monitoring using the AWS CLI, in the following commands, set the `--monitoring-interval` option to a value other than `0` and set the `--monitoring-role-arn` option to the role you created in [Creating an IAM role for Enhanced Monitoring](#USER_Monitoring.OS.Enabling.Prerequisites).
+ [create-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-instance.html)
+ [create-db-instance-read-replica](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-instance-read-replica.html)
+ [modify-db-instance](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-instance.html)
+ [create-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/create-db-cluster.html) (Multi-AZ DB cluster)
+ [modify-db-cluster](https://docs.aws.amazon.com/cli/latest/reference/rds/modify-db-cluster.html) (Multi-AZ DB cluster)
The `--monitoring-interval` option specifies the interval, in seconds, between points when Enhanced Monitoring metrics are collected. Valid values for the option are `0`, `1`, `5`, `10`, `15`, `30`, and `60`.
To turn off Enhanced Monitoring using the AWS CLI, set the `--monitoring-interval` option to `0` in these commands.
**Example**
The following example turns on Enhanced Monitoring for a DB instance:
For Linux, macOS, or Unix:
```
aws rds modify-db-instance \
--db-instance-identifier mydbinstance \
--monitoring-interval 30 \
--monitoring-role-arn arn:aws:iam::123456789012:role/emaccess
```
For Windows:
```
aws rds modify-db-instance ^
--db-instance-identifier mydbinstance ^
--monitoring-interval 30 ^
--monitoring-role-arn arn:aws:iam::123456789012:role/emaccess
```
**Example**
The following example turns on Enhanced Monitoring for a Multi-AZ DB cluster:
For Linux, macOS, or Unix:
```
aws rds modify-db-cluster \
--db-cluster-identifier mydbcluster \
--monitoring-interval 30 \
--monitoring-role-arn arn:aws:iam::123456789012:role/emaccess
```
For Windows:
```
aws rds modify-db-cluster ^
--db-cluster-identifier mydbcluster ^
--monitoring-interval 30 ^
--monitoring-role-arn arn:aws:iam::123456789012:role/emaccess
```
### RDS API
To turn on Enhanced Monitoring using the RDS API, set the `MonitoringInterval` parameter to a value other than `0` and set the `MonitoringRoleArn` parameter to the role you created in [Creating an IAM role for Enhanced Monitoring](#USER_Monitoring.OS.Enabling.Prerequisites). Set these parameters in the following actions:
+ [CreateDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBInstance.html)
+ [CreateDBInstanceReadReplica](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBInstanceReadReplica.html)
+ [ModifyDBInstance](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBInstance.html)
+ [CreateDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_CreateDBCluster.html) (Multi-AZ DB cluster)
+ [ModifyDBCluster](https://docs.aws.amazon.com/AmazonRDS/latest/APIReference/API_ModifyDBCluster.html) (Multi-AZ DB cluster)
The `MonitoringInterval` parameter specifies the interval, in seconds, between points when Enhanced Monitoring metrics are collected. Valid values are `0`, `1`, `5`, `10`, `15`, `30`, and `60`.
To turn off Enhanced Monitoring using the RDS API, set `MonitoringInterval` to `0`.
## Protecting against the confused deputy problem
The confused deputy problem is a security issue where an entity that doesn't have permission to perform an action can coerce a more-privileged entity to perform the action. In AWS, cross-service impersonation can result in the confused deputy problem. Cross-service impersonation can occur when one service (the *calling service*) calls another service (the *called service*). The calling service can be manipulated to use its permissions to act on another customer's resources in a way it should not otherwise have permission to access. To prevent this, AWS provides tools that help you protect your data for all services with service principals that have been given access to resources in your account. For more information, see [The confused deputy problem](https://docs.aws.amazon.com/IAM/latest/UserGuide/confused-deputy.html).
To limit the permissions to the resource that Amazon RDS can give another service, we recommend using the `aws:SourceArn` and `aws:SourceAccount` global condition context keys in a trust policy for your Enhanced Monitoring role. If you use both global condition context keys, they must use the same account ID.
The most effective way to protect against the confused deputy problem is to use the `aws:SourceArn` global condition context key with the full ARN of the resource. For Amazon RDS, set `aws:SourceArn` to `arn:aws:rds:Region:my-account-id:db:dbname`.
The following example uses the `aws:SourceArn` and `aws:SourceAccount` global condition context keys in a trust policy to prevent the confused deputy problem.
------
#### [ JSON ]
****
```
{
"Version":"2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "monitoring.rds.amazonaws.com"
},
"Action": "sts:AssumeRole",
"Condition": {
"StringLike": {
"aws:SourceArn": "arn:aws:rds:Region:my-123456789012:db:dbname"
},
"StringEquals": {
"aws:SourceAccount": "my-123456789012"
}
}
}
]
}
```
------
# Viewing OS metrics in the RDS console
You can view OS metrics reported by Enhanced Monitoring in the RDS console by choosing **Enhanced monitoring** for **Monitoring**.
The following example shows the Enhanced Monitoring page. For descriptions of the Enhanced Monitoring metrics, see [OS metrics in Enhanced Monitoring](USER_Monitoring-Available-OS-Metrics.md).
![\[Dashboard view\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/metrics1.png)
Some DB instances use more than one disk for the DB instance's data storage volume. On those DB instances, the **Physical Devices** graphs show metrics for each one of the disks. For example, the following graph shows metrics for four disks.
![\[Graph with multiple disks\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/enhanced-monitoring-multiple-disks.png)
**Note**
Currently, **Physical Devices** graphs are not available for Microsoft SQL Server DB instances.
When you are viewing aggregated **File system** graphs, the **rdsdbdata\$1** device relates to the `rdsfilesys/rdsdbdata*` file system, where all database files and logs are stored. The **rootfilesys** device relates to the `/` file system (also known as root), where files related to the operating system are stored. When using additional storage volumes, view the `rdsdbdata2`, `rdsdbdata3`, and `rdsdbdata4` volume metrics for volume specific information.
When you are viewing aggregated **Disk I/O** graphs, the **rdsdbdata** device relates to the primary `/rdsdbdata` storage volume. When using additional storage volumes, view the `rdsdbdata2`, `rdsdbdata3`, and `rdsdbdata4` volume metrics for volume specific information. The filesystem device relates to the /file system (also known as root), where files related to the operating system are stored.
The **rdsdev** device name is deprecated. The **rdsdev** device only relates to the primary `/rdsdbdata` storage volume and does not include metrics from additional storage volumes.
![\[Graph showing file system usage\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/enhanced-monitoring-filesystem.png)
If the DB instance is a Multi-AZ deployment, you can view the OS metrics for the primary DB instance and its Multi-AZ standby replica. In the **Enhanced monitoring** view, choose **primary** to view the OS metrics for the primary DB instance, or choose **secondary** to view the OS metrics for the standby replica.
![\[Primary and secondary choice for Enhanced Monitoring\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/enhanced-monitoring-primary-secondary.png)
For more information about Multi-AZ deployments, see [Configuring and managing a Multi-AZ deployment for Amazon RDS](Concepts.MultiAZ.md).
**Note**
Currently, viewing OS metrics for a Multi-AZ standby replica is not supported for MariaDB DB instances.
If you want to see details for the processes running on your DB instance, choose **OS process list** for **Monitoring**.
The **Process List** view is shown following.
![\[Process list view\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/metrics2.png)
The Enhanced Monitoring metrics shown in the **Process list** view are organized as follows:
+ **RDS child processes** – Shows a summary of the RDS processes that support the DB instance, for example `mysqld` for MySQL DB instances. Process threads appear nested beneath the parent process. Process threads show CPU utilization only as other metrics are the same for all threads for the process. The console displays a maximum of 100 processes and threads. The results are a combination of the top CPU consuming and memory consuming processes and threads. If there are more than 50 processes and more than 50 threads, the console displays the top 50 consumers in each category. This display helps you identify which processes are having the greatest impact on performance.
+ **RDS processes** – Shows a summary of the resources used by the RDS management agent, diagnostics monitoring processes, and other AWS processes that are required to support RDS DB instances.
+ **OS processes** – Shows a summary of the kernel and system processes, which generally have minimal impact on performance.
The items listed for each process are:
+ **VIRT** – Displays the virtual size of the process.
+ **RES** – Displays the actual physical memory being used by the process.
+ **CPU%** – Displays the percentage of the total CPU bandwidth being used by the process.
+ **MEM%** – Displays the percentage of the total memory being used by the process.
The monitoring data that is shown in the RDS console is retrieved from Amazon CloudWatch Logs. You can also retrieve the metrics for a DB instance as a log stream from CloudWatch Logs. For more information, see [Viewing OS metrics using CloudWatch Logs](USER_Monitoring.OS.CloudWatchLogs.md).
Enhanced Monitoring metrics are not returned during the following:
+ A failover of the DB instance.
+ Changing the instance class of the DB instance (scale compute).
Enhanced Monitoring metrics are returned during a reboot of a DB instance because only the database engine is rebooted. Metrics for the operating system are still reported.
# Viewing OS metrics using CloudWatch Logs
After you have enabled Enhanced Monitoring for your DB instance or Multi-AZ DB cluster, you can view the metrics for it using CloudWatch Logs, with each log stream representing a single DB instance or DB cluster being monitored. The log stream identifier is the resource identifier (`DbiResourceId`) for the DB instance or DB cluster.
**To view Enhanced Monitoring log data**
1. Open the CloudWatch console at [https://console.aws.amazon.com/cloudwatch/](https://console.aws.amazon.com/cloudwatch/).
1. If necessary, choose the AWS Region that your DB instance or Multi-AZ DB cluster is in. For more information, see [Regions and endpoints](https://docs.aws.amazon.com/general/latest/gr/index.html?rande.html) in the *Amazon Web Services General Reference*.
1. Choose **Logs** in the navigation pane.
1. Choose **RDSOSMetrics** from the list of log groups.
In a Multi-AZ DB instance deployment, log files with `-secondary` appended to the name are for the Multi-AZ standby replica.
![\[Multi-AZ standby replica log file\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/images/enhanced-monitoring-cloudwatch-secondary.png)
1. Choose the log stream that you want to view from the list of log streams.
# Metrics reference for Amazon RDS
In this reference, you can find descriptions of Amazon RDS metrics for Amazon CloudWatch, Performance Insights, and Enhanced Monitoring.
**Topics**
+ [
# Amazon CloudWatch metrics for Amazon RDS
](rds-metrics.md)
+ [
# Amazon CloudWatch dimensions for Amazon RDS
](dimensions.md)
+ [
# Amazon CloudWatch metrics for Amazon RDS Performance Insights
](USER_PerfInsights.Cloudwatch.md)
+ [
# Performance Insights counter metrics
](USER_PerfInsights_Counters.md)
+ [
# SQL statistics for Performance Insights
](sql-statistics.md)
+ [
# OS metrics in Enhanced Monitoring
](USER_Monitoring-Available-OS-Metrics.md)
# Amazon CloudWatch metrics for Amazon RDS
Amazon CloudWatch metrics provide insights into the performance and health of Amazon RDS instances and clusters, allowing you to monitor system behavior and make data-driven decisions. These metrics help track resource utilization, database activity, and operational efficiency, offering visibility into how your instances are performing.
This reference outlines the specific metrics available for Amazon RDS and explains how to interpret and use them to optimize database performance, troubleshoot issues, and ensure high availability.
Amazon RDS publishes metrics to Amazon CloudWatch in the `AWS/RDS` and `AWS/Usage` namespaces.
**Topics**
+ [
## Amazon CloudWatch instance-level metrics for Amazon RDS
](#rds-cw-metrics-instance)
+ [
## Amazon CloudWatch usage metrics for Amazon RDS
](#rds-metrics-usage)
## Amazon CloudWatch instance-level metrics for Amazon RDS
The `AWS/RDS` namespace in Amazon CloudWatch includes the following instance-level metrics.
**Note**
The Amazon RDS console might display metrics in units that are different from the units sent to Amazon CloudWatch. For example, the Amazon RDS console might display a metric in megabytes (MB), while the metric is sent to Amazon CloudWatch in bytes.
| Metric | Description | Applies to | Units |
| --- | --- | --- | --- |
| `BinLogDiskUsage` | The amount of disk space occupied by binary logs. If automatic backups are enabled for MySQL and MariaDB instances, including read replicas, binary logs are created. | MariaDB MySQL | Bytes |
| `BurstBalance` | The percent of General Purpose SSD (gp2) burst-bucket I/O credits available. | All | Percent |
| `CheckpointLag` | The amount of time since the most recent checkpoint. | | Seconds |
| `ConnectionAttempts` | The number of attempts to connect to an instance, whether successful or not. | MySQL | Count |
| `CPUUtilization` | The percentage of CPU utilization. | All | Percent |
| `CPUCreditUsage` | The number of CPU credits spent by the instance for CPU utilization. One CPU credit equals one vCPU running at 100 percent utilization for one minute or an equivalent combination of vCPUs, utilization, and time. For example, you might have one vCPU running at 50 percent utilization for two minutes or two vCPUs running at 25 percent utilization for two minutes.This metric applies only to db.t2, db.t3, and db.t4g instances. We recommend using the T DB instance classes only for development and test servers, or other non-production servers. For more details on the T instance classes, see [DB instance class types](Concepts.DBInstanceClass.Types.md) CPU credit metrics are available at a five-minute frequency only. If you specify a period greater than five minutes, use the `Sum` statistic instead of the `Average` statistic. | | Credits (vCPU-minutes) |
| `CPUCreditBalance` | The number of earned CPU credits that an instance has accrued since it was launched or started. For T2 Standard, the `CPUCreditBalance` also includes the number of launch credits that have been accrued.Credits are accrued in the credit balance after they are earned, and removed from the credit balance when they are spent. The credit balance has a maximum limit, determined by the instance size. After the limit is reached, any new credits that are earned are discarded. For T2 Standard, launch credits don't count towards the limit.The credits in the `CPUCreditBalance` are available for the instance to spend to burst beyond its baseline CPU utilization.When an instance is running, credits in the `CPUCreditBalance` don't expire. When the instance stops, the `CPUCreditBalance` does not persist, and all accrued credits are lost.CPU credit metrics are available at a five-minute frequency only.This metric applies only to db.t2, db.t3, and db.t4g instances. We recommend using the T DB instance classes only for development and test servers, or other non-production servers. For more details on the T instance classes, see [DB instance class types](Concepts.DBInstanceClass.Types.md) Launch credits work the same way in Amazon RDS as they do in Amazon EC2. For more information, see [Launch credits](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/burstable-performance-instances-standard-mode-concepts.html#launch-credits) in the *Amazon Elastic Compute Cloud User Guide for Linux Instances*. | | Credits (vCPU-minutes) |
| `CPUSurplusCreditBalance` | The number of surplus credits that have been spent by an unlimited instance when its `CPUCreditBalance` value is zero. The `CPUSurplusCreditBalance` value is paid down by earned CPU credits. If the number of surplus credits exceeds the maximum number of credits that the instance can earn in a 24-hour period, the spent surplus credits above the maximum incur an additional charge. CPU credit metrics are available at a 5-minute frequency only. | All | Credits (vCPU-minutes) |
| `CPUSurplusCreditsCharged` | The number of spent surplus credits that are not paid down by earned CPU credits, and which thus incur an additional charge. Spent surplus credits are charged when any of the following occurs: [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-metrics.html) CPU credit metrics are available at a 5-minute frequency only. | All | Credits (vCPU-minutes) |
| `DatabaseConnections` | The number of client network connections to the database instance. The number of database sessions can be higher than the metric value because the metric value doesn't include the following: [\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/rds-metrics.html) | All | Count |
| `DiskQueueDepth` | The number of outstanding I/Os (read/write requests) waiting to access the disk. | All | Count |
| `DiskQueueDepthLogVolume` | The number of outstanding I/Os (read/write requests) waiting to access the log volume disk. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Count |
| `EBSByteBalance%` | The percentage of throughput credits remaining in the burst bucket of your RDS database. This metric is available for basic monitoring only. The metric value is based on the throughput of all volumes, including the root volume, rather than on only those volumes containing database files. To find the instance sizes that support this metric, see the instance sizes with an asterisk (\$1) in the [EBS optimized by default](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-optimized.html#current) table in *Amazon EC2 User Guide*. The `Sum` statistic is not applicable to this metric. | All | Percent |
| `EBSIOBalance%` | The percentage of I/O credits remaining in the burst bucket of your RDS database. This metric is available for basic monitoring only. The metric value is based on the IOPS of all volumes, including the root volume, rather than on only those volumes containing database files. To find the instance sizes that support this metric, see [Amazon EBS–optimized instance types](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/ebs-optimized.html) in *Amazon EC2 User Guide*. The `Sum` statistic isn't applicable to this metric. This metric is different from `BurstBalance`. To learn how to use this metric, see [Improving application performance and reducing costs with Amazon EBS-Optimized Instance burst capability](https://aws.amazon.com/blogs/compute/improving-application-performance-and-reducing-costs-with-amazon-ebs-optimized-instance-burst-capability/). | All | Percent |
| `FailedSQLServerAgentJobsCount` | The number of failed Microsoft SQL Server Agent jobs during the last minute. | Microsoft SQL Server | Count per minute |
| `FreeableMemory` | The amount of available random access memory. For MariaDB, MySQL, Oracle, and PostgreSQL DB instances, this metric reports the value of the `MemAvailable` field of `/proc/meminfo`. | All | Bytes |
| `FreeLocalStorage` | The amount of available local storage space. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Bytes |
| `FreeLocalStoragePercent` | The percentage of available local storage space. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Percent |
| `FreeStorageSpace` | The amount of available storage space. | All | Bytes |
| `FreeStorageSpaceLogVolume` | The amount of available storage space on the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Bytes |
| `IamDbAuthConnectionRequests` | The number of connection requests using IAM authentication to the DB instance. | All | Count |
| `MaximumUsedTransactionIDs` | The maximum transaction IDs that have been used. | PostgreSQL | Count |
| `NetworkReceiveThroughput` | The incoming (receive) network traffic on the DB instance, including both customer database traffic and Amazon RDS traffic used for monitoring and replication. | All | Bytes per second |
| `NetworkTransmitThroughput` | The outgoing (transmit) network traffic on the DB instance, including both customer database traffic and Amazon RDS traffic used for monitoring and replication. | All | Bytes per second |
| `OldestLogicalReplicationSlotLag` | The lagging size of the Amazon RDS commits a transaction on the source database and the time when RDS applies the transaction on the replica database. | PostgreSQL | Bytes |
| `OldestReplicationSlotLag` | The lagging size of the replica lagging the most in terms of write-ahead log (WAL) data received. | PostgreSQL | Bytes |
| `ReadIOPS` | The average number of disk read I/O operations per second. | All | Count per second |
| `ReadIOPSLocalStorage` | The average number of disk read I/O operations to local storage per second. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Count per second |
| `ReadIOPSLogVolume` | The average number of disk read I/O operations per second for the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Count per second |
| `ReadLatency` | The average amount of time taken per disk I/O operation. | All | Seconds |
| `ReadLatencyLocalStorage` | The average amount of time taken per disk I/O operation for local storage. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Seconds |
| `ReadLatencyLogVolume` | The average amount of time taken per disk I/O operation for the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Seconds |
| `ReadThroughput` | The average number of bytes read from disk per second. | All | Bytes per second |
| `ReadThroughputLocalStorage` | The average number of bytes read from disk per second for local storage. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Bytes per second |
| `ReadThroughputLogVolume` | The average number of bytes read from disk per second for the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Bytes per second |
| `ReplicaLag` | For read replica configurations, the amount of time a read replica DB instance lags behind the source DB instance. Applies to MariaDB, Microsoft SQL Server, MySQL, Oracle, and PostgreSQL read replicas. For Multi-AZ DB clusters, the difference in time between the latest transaction on the writer DB instance and the latest applied transaction on a reader DB instance. | | Seconds |
| `ReplicationChannelLag` | For multi-source replica configurations, the amount of time a particular channel on the multi-source replica lags behind the source DB instance. For more information, see [Monitoring multi-source replication channels](mysql-multi-source-replication.md#mysql-multi-source-replication-monitoring). | MySQL | Seconds |
| `ReplicationSlotDiskUsage` | The disk space used by replication slot files. | PostgreSQL | Bytes |
| `SwapUsage` | The amount of swap space used on the DB instance. | MariaDB MySQL Oracle PostgreSQL | Bytes |
| `TempDbAvailableDataSpace` | The amount of available data space on the tempdb and the volume where tempdb is located. Use this metric to monitor tempdb data space availability and plan capacity accordingly. Low values may indicate the need to increase storage or optimize queries that heavily use tempdb. | SQL Server | Bytes |
| `TempDbAvailableLogSpace` | The amount of available log space on the tempdb and the volume where tempdb is located. Use this metric to monitor tempdb log space availability and prevent transaction log full conditions. Critical for workloads with large transactions or high concurrency that generate significant log activity. | SQL Server | Bytes |
| `TempDbDataFileUsage` | The percentage of data files used on the tempdb. This metric doesn't account for potential file growth. Use this metric to monitor tempdb data file utilization and identify potential performance bottlenecks. High values may indicate the need to optimize queries that create large temporary objects or increase tempdb size. | SQL Server | Percent |
| `TempDbLogFileUsage` | The percentage of log files used on the tempdb. This metric doesn't account for potential file growth. Use this metric to monitor tempdb log file utilization and prevent performance issues. High values may indicate long-running transactions or excessive logging activity that could impact overall database performance. | SQL Server | Percent |
| `TransactionLogsDiskUsage` | The disk space used by transaction logs. | PostgreSQL | Bytes |
| `TransactionLogsGeneration` | The size of transaction logs generated per second. | PostgreSQL | Bytes per second |
| `WriteIOPS` | The average number of disk write I/O operations per second. | All | Count per second |
| `WriteIOPSLocalStorage` | The average number of disk write I/O operations per second on local storage. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Count per second |
| `WriteIOPSLogVolume` | The average number of disk write I/O operations per second for the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Count per second |
| `WriteLatency` | The average amount of time taken per disk I/O operation. | All | Seconds |
| `WriteLatencyLocalStorage` | The average amount of time taken per disk I/O operation on local storage. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Seconds |
| `WriteLatencyLogVolume` | The average amount of time taken per disk I/O operation for the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Seconds |
| `WriteThroughput` | The average number of bytes written to disk per second. | All | Bytes per second |
| `WriteThroughputLogVolume` | The average number of bytes written to disk per second for the log volume. | DB instances with [dedicated log volume](USER_PIOPS.dlv.md) enabled | Bytes per second |
| `WriteThroughputLocalStorage` | The average number of bytes written to disk per second for local storage. This metric only applies to DB instance classes with NVMe SSD instance store volumes. For information about Amazon EC2 instances with NVMe SSD instance store volumes, see [ Instance store volumes](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/InstanceStorage.html#instance-store-volumes). The equivalent RDS DB instance classes have the same instance store volumes. For example, the db.m6gd and db.r6gd DB instance classes have NVMe SSD instance store volumes. | | Bytes per second |
## Amazon CloudWatch usage metrics for Amazon RDS
The `AWS/Usage` namespace in Amazon CloudWatch includes account-level usage metrics for your Amazon RDS service quotas. CloudWatch collects usage metrics automatically for all AWS Regions.
For more information, see [CloudWatch usage metrics](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch-Usage-Metrics.html) in the *Amazon CloudWatch User Guide*. For more information about quotas, see [Quotas and constraints for Amazon RDS](CHAP_Limits.md) and [Requesting a quota increase](https://docs.aws.amazon.com/servicequotas/latest/userguide/request-quota-increase.html) in the *Service Quotas User Guide*.
| Metric | Description | Units\$1 |
| --- | --- | --- |
| AllocatedStorage | The total storage for all DB instances. The sum excludes temporary migration instances. | Gigabytes |
| AuthorizationsPerDBSecurityGroup | The number of ingress rules per DB security group in your AWS account. The used value is the highest number of ingress rules in a DB security group in the account. Other DB security groups in the account might have a lower number of ingress rules. | Count |
| CustomEndpointsPerDBCluster | The number of custom endpoints per DB cluster in your AWS account. The used value is the highest number of custom endpoints in a DB cluster in the account. Other DB clusters in the account might have a lower number of custom endpoints. | Count |
| CustomEngineVersions | The number of custom engine versions (CEVs) for Amazon RDS Custom in your AWS account. | Count |
| DBClusterParameterGroups | The number of DB cluster parameter groups in your AWS account. The count excludes default parameter groups. | Count |
| DBClusterRoles | The number of associated AWS Identity and Access Management (IAM) roles per DB cluster in your AWS account. The used value is the highest number of associated IAM roles for a DB cluster in the account. Other DB clusters in the account might have a lower number of associated IAM roles. | Count |
| DBClusters | The number of Amazon Aurora DB clusters in your AWS account. | Count |
| DBInstanceRoles | The number of associated AWS Identity and Access Management (IAM) roles per DB instance in your AWS account. The used value is the highest number of associated IAM roles for a DB instance in the account. Other DB instances in the account might have a lower number of associated IAM roles. | Count |
| DBInstances | The number of DB instances in your AWS account. | Count |
| DBParameterGroups | The number of DB parameter groups in your AWS account. The count excludes the default DB parameter groups. | Count |
| DBSecurityGroups | The number of security groups in your AWS account. The count excludes the default security group and the default VPC security group. | Count |
| DBSubnetGroups | The number of DB subnet groups in your AWS account. The count excludes the default subnet group. | Count |
| EventSubscriptions | The number of event notification subscriptions in your AWS account. | Count |
| Integrations | The number of zero-ETL integrations with Amazon Redshift in your AWS account. | Count |
| ManualClusterSnapshots | The number of manually created DB cluster snapshots in your AWS account. The count excludes invalid snapshots. | Count |
| ManualSnapshots | The number of manually created DB snapshots in your AWS account. The count excludes invalid snapshots. | Count |
| OptionGroups | The number of option groups in your AWS account. The count excludes the default option groups. | Count |
| Proxies | The number of RDS proxies in your AWS account. | Count |
| ReadReplicasPerMaster | The number of read replicas per DB instance in your account. The used value is the highest number of read replicas for a DB instance in the account. Other DB instances in the account might have a lower number of read replicas. | Count |
| ReservedDBInstances | The number of reserved DB instances in your AWS account. The count excludes retired or declined instances. | Count |
| SubnetsPerDBSubnetGroup | The number of subnets per DB subnet group in your AWS account. The highest number of subnets for a DB subnet group in the account. Other DB subnet groups in the account might have a lower number of subnets. | Count |
**Note**
Amazon RDS doesn't publish units for usage metrics to CloudWatch. The units only appear in the documentation.
# Amazon CloudWatch dimensions for Amazon RDS
You can filter Amazon RDS metrics data by using any dimension in the following table.
| Dimension | Filters the requested data for . . . |
| --- | --- |
| DBInstanceIdentifier | A specific DB instance. |
| DatabaseClass | All instances in a database class. For example, you can aggregate metrics for all instances that belong to the database class `db.r5.large`. |
| EngineName | The identified engine name only. For example, you can aggregate metrics for all instances that have the engine name `postgres`. |
| SourceRegion | The specified Region only. For example, you can aggregate metrics for all DB instances in the `us-east-1` Region. |
| DbInstanceIdentifier, VolumeName | The metrics per-volume for a single instance. RDS captures metrics for multiple storage volumes. |
**Note**
If you are using additional storage volumes, you can see aggregate storage metrics under the `DBInstanceIdentifier` dimension. To see per-volume storage metrics, use the `DbInstanceIdentifier, VolumeName` dimensions.
# Amazon CloudWatch metrics for Amazon RDS Performance Insights
Performance Insights automatically publishes some metrics to Amazon CloudWatch. The same data can be queried from Performance Insights, but having the metrics in CloudWatch makes it easy to add CloudWatch alarms. It also makes it easy to add the metrics to existing CloudWatch Dashboards.
| Metric | Description |
| --- | --- |
| DBLoad | The number of active sessions for the database. Typically, you want the data for the average number of active sessions. In Performance Insights, this data is queried as `db.load.avg`. |
| DBLoadCPU | The number of active sessions where the wait event type is CPU. In Performance Insights, this data is queried as `db.load.avg`, filtered by the wait event type `CPU`. |
| DBLoadNonCPU | The number of active sessions where the wait event type is not CPU. |
| DBLoadRelativeToNumVCPUs | The ratio of the DB load to the number of virtual CPUs for the database. |
**Note**
These metrics are published to CloudWatch only if there is load on the DB instance.
You can examine these metrics using the CloudWatch console, the AWS CLI, or the CloudWatch API. You can also examine other Performance Insights counter metrics using a special metric math function. For more information, see [Querying other Performance Insights counter metrics in CloudWatch](#USER_PerfInsights.Cloudwatch.ExtraMetrics).
For example, you can get the statistics for the `DBLoad` metric by running the [get-metric-statistics](https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/get-metric-statistics.html) command.
```
aws cloudwatch get-metric-statistics \
--region us-west-2 \
--namespace AWS/RDS \
--metric-name DBLoad \
--period 60 \
--statistics Average \
--start-time 1532035185 \
--end-time 1532036185 \
--dimensions Name=DBInstanceIdentifier,Value=db-loadtest-0
```
This example generates output similar to the following.
```
{
"Datapoints": [
{
"Timestamp": "2021-07-19T21:30:00Z",
"Unit": "None",
"Average": 2.1
},
{
"Timestamp": "2021-07-19T21:34:00Z",
"Unit": "None",
"Average": 1.7
},
{
"Timestamp": "2021-07-19T21:35:00Z",
"Unit": "None",
"Average": 2.8
},
{
"Timestamp": "2021-07-19T21:31:00Z",
"Unit": "None",
"Average": 1.5
},
{
"Timestamp": "2021-07-19T21:32:00Z",
"Unit": "None",
"Average": 1.8
},
{
"Timestamp": "2021-07-19T21:29:00Z",
"Unit": "None",
"Average": 3.0
},
{
"Timestamp": "2021-07-19T21:33:00Z",
"Unit": "None",
"Average": 2.4
}
],
"Label": "DBLoad"
}
```
For more information about CloudWatch, see [What is Amazon CloudWatch?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/WhatIsCloudWatch.html) in the *Amazon CloudWatch User Guide*.
## Querying other Performance Insights counter metrics in CloudWatch
**Note**
If you enable the Advanced mode of Database Insights, Amazon RDS publishes Performance Insights counter metrics to Amazon CloudWatch. With Database Insights, you don't need to use the `DB_PERF_INSIGHTS` metric math function. You can use the CloudWatch Database Insights dashboard to search, query, and set alarms for Performance Insights counter metrics.
You can query, alarm, and graphs on RDS Performance Insights metrics from CloudWatch. You can access information about your DB instance by using the `DB_PERF_INSIGHTS` metric math function for CloudWatch. This function allows you to use the Performance Insights metrics that are not directly reported to CloudWatch to create a new time series.
You can use the new Metric Math function by clicking on the **Add Math** drop-down menu in the **Select metric** screen in the CloudWatch console. You can use it to create alarms and graphs on Performance Insights metrics or on combinations of CloudWatch and Performance Insights metrics, including high-resolution alarms for sub-minute metrics. You can also use the function programmatically by including the Metric Math expression in a [https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/get-metric-data.html](https://docs.aws.amazon.com/cli/latest/reference/cloudwatch/get-metric-data.html) request. For more information, see [Metric math syntax and functions](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/using-metric-math.html#metric-math-syntax-functions-list) and [Create an alarm on Performance Insights counter metrics from an AWS database](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_alarm_database_performance_insights.html).
# Performance Insights counter metrics
Counter metrics are operating system and database performance metrics in the Performance Insights dashboard. To help identify and analyze performance problems, you can correlate counter metrics with DB load. You must append a statistic function to the metric to get the metric values. For example, the supported functions for `os.memory.active` metric are `.avg`, `.min`, `.max`, `.sum`, and `.sample_count`.
The counter metrics are collected one time each minute. The OS metrics collection depends on whether Enhanced Monitoring is turned on or off. If Enhanced Monitoring is turned off, the OS metrics are collected one time each minute. If Enhanced Monitoring is turned on, the OS metrics are collected for the selected time period. For more information about turning Enhanced Monitoring on or off, see [Turning Enhanced Monitoring on and off](USER_Monitoring.OS.Enabling.md#USER_Monitoring.OS.Enabling.Procedure).
**Topics**
+ [
## Performance Insights operating system counters
](#USER_PerfInsights_Counters.OS)
+ [
## Performance Insights counters for Amazon RDS for MariaDB and MySQL
](#USER_PerfInsights_Counters.MySQL)
+ [
## Performance Insights counters for Amazon RDS for Microsoft SQL Server
](#USER_PerfInsights_Counters.SQLServer)
+ [
## Performance Insights counters for Amazon RDS for Oracle
](#USER_PerfInsights_Counters.Oracle)
+ [
## Performance Insights counters for Amazon RDS for PostgreSQL
](#USER_PerfInsights_Counters.PostgreSQL)
## Performance Insights operating system counters
The following operating system counters, which are prefixed with `os`, are available with Performance Insights for all RDS engines except RDS for SQL Server .
You can use `ListAvailableResourceMetrics` API for the list of available counter metrics for your DB instance. For more information, see [ ListAvailableResourceMetrics](https://docs.aws.amazon.com/performance-insights/latest/APIReference/API_ListAvailableResourceMetrics) in the Amazon RDS Performance Insights API Reference guide.
| Counter | Type | Unit | Metric | Description |
| --- | --- | --- | --- | --- |
| Active | Memory | Kilobytes | os.memory.active | The amount of assigned memory, in kilobytes. |
| Buffers | Memory | Kilobytes | os.memory.buffers | The amount of memory used for buffering I/O requests prior to writing to the storage device, in kilobytes. |
| Cached | Memory | Kilobytes | os.memory.cached | The amount of memory used for caching file system–based I/O, in kilobytes. |
| DB Cache | Memory | Bytes | os.memory.db.cache | The amount of memory used for page cache by database process including tmpfs (shmem), in bytes. |
| DB Resident Set Size | Memory | Bytes | os.memory.db.residentSetSize | The amount of memory used for anonymous and swap cache by database process not including tmpfs (shmem), in bytes. |
| DB Swap | Memory | Bytes | os.memory.db.swap | The amount of memory used for swap by database process, in bytes. |
| Dirty | Memory | Kilobytes | os.memory.dirty | The amount of memory pages in RAM that have been modified but not written to their related data block in storage, in kilobytes. |
| Free | Memory | Kilobytes | os.memory.free | The amount of unassigned memory, in kilobytes. |
| Huge Pages Free | Memory | Pages | os.memory.hugePagesFree | The number of free huge pages. Huge pages are a feature of the Linux kernel. |
| Huge Pages Rsvd | Memory | Pages | os.memory.hugePagesRsvd | The number of committed huge pages. |
| Huge Pages Size | Memory | Kilobytes | os.memory.hugePagesSize | The size for each huge pages unit, in kilobytes. |
| Huge Pages Surp | Memory | Pages | os.memory.hugePagesSurp | The number of available surplus huge pages over the total. |
| Huge Pages Total | Memory | Pages | os.memory.hugePagesTotal | The total number of huge pages. |
| Inactive | Memory | Kilobytes | os.memory.inactive | The amount of least-frequently used memory pages, in kilobytes. |
| Mapped | Memory | Kilobytes | os.memory.mapped | The total amount of file-system contents that is memory mapped inside a process address space, in kilobytes. |
| Out of Memory Kill Count | Memory | Kills | os.memory.outOfMemoryKillCount | The number of OOM kills that happened over the last collection interval. |
| Page Tables | Memory | Kilobytes | os.memory.pageTables | The amount of memory used by page tables, in kilobytes. |
| Slab | Memory | Kilobytes | os.memory.slab | The amount of reusable kernel data structures, in kilobytes. |
| Total | Memory | Kilobytes | os.memory.total | The total amount of memory, in kilobytes. |
| Writeback | Memory | Kilobytes | os.memory.writeback | The amount of dirty pages in RAM that are still being written to the backing storage, in kilobytes. |
| Guest | Cpu Utilization | Percentage | os.cpuUtilization.guest | The percentage of CPU in use by guest programs. |
| Idle | Cpu Utilization | Percentage | os.cpuUtilization.idle | The percentage of CPU that is idle. |
| Irq | Cpu Utilization | Percentage | os.cpuUtilization.irq | The percentage of CPU in use by software interrupts. |
| Nice | Cpu Utilization | Percentage | os.cpuUtilization.nice | The percentage of CPU in use by programs running at lowest priority. |
| Steal | Cpu Utilization | Percentage | os.cpuUtilization.steal | The percentage of CPU in use by other virtual machines. |
| System | Cpu Utilization | Percentage | os.cpuUtilization.system | The percentage of CPU in use by the kernel. |
| Total | Cpu Utilization | Percentage | os.cpuUtilization.total | The total percentage of the CPU in use. This value includes the nice value. |
| User | Cpu Utilization | Percentage | os.cpuUtilization.user | The percentage of CPU in use by user programs. |
| Wait | Cpu Utilization | Percentage | os.cpuUtilization.wait | The percentage of CPU unused while waiting for I/O access. |
| Read IOs PS | Disk IO | Requests per second | os.diskIO..readIOsPS | The number of read operations per second. |
| Write IOs PS | Disk IO | Requests per second | os.diskIO..writeIOsPS | The number of write operations per second. |
| Avg Queue Len | Disk IO | Requests | os.diskIO..avgQueueLen | The number of requests waiting in the I/O device's queue. |
| Avg Req Sz | Disk IO | Requests | os.diskIO..avgReqSz | The number of requests waiting in the I/O device's queue. |
| Await | Disk IO | Milliseconds | os.diskIO..await | The number of milliseconds required to respond to requests, including queue time and service time. |
| Read IOs PS | Disk IO | Requests | os.diskIO..readIOsPS | The number of read operations per second. |
| Read KB | Disk IO | Kilobytes | os.diskIO..readKb | The total number of kilobytes read. |
| Read KB PS | Disk IO | Kilobytes per second | os.diskIO..readKbPS | The number of kilobytes read per second. |
| Rrqm PS | Disk IO | Requests per second | os.diskIO..rrqmPS | The number of merged read requests queued per second. |
| TPS | Disk IO | Transactions per second | os.diskIO..tps | The number of I/O transactions per second. |
| Util | Disk IO | Percentage | os.diskIO..util | The percentage of CPU time during which requests were issued. |
| Write KB | Disk IO | Kilobytes | os.diskIO..writeKb | The total number of kilobytes written. |
| Write KB PS | Disk IO | Kilobytes per second | os.diskIO..writeKbPS | The number of kilobytes written per second. |
| Wrqm PS | Disk IO | Requests per second | os.diskIO..wrqmPS | The number of merged write requests queued per second. |
| Blocked | Tasks | Tasks | os.tasks.blocked | The number of tasks that are blocked. |
| Running | Tasks | Tasks | os.tasks.running | The number of tasks that are running. |
| Sleeping | Tasks | Tasks | os.tasks.sleeping | The number of tasks that are sleeping. |
| Stopped | Tasks | Tasks | os.tasks.stopped | The number of tasks that are stopped. |
| Total | Tasks | Tasks | os.tasks.total | The total number of tasks. |
| Zombie | Tasks | Tasks | os.tasks.zombie | The number of child tasks that are inactive with an active parent task. |
| One | Load Average Minute | Processes | os.loadAverageMinute.one | The number of processes requesting CPU time over the last minute. |
| Fifteen | Load Average Minute | Processes | os.loadAverageMinute.fifteen | The number of processes requesting CPU time over the last 15 minutes. |
| Five | Load Average Minute | Processes | os.loadAverageMinute.five | The number of processes requesting CPU time over the last 5 minutes. |
| Cached | Swap | Kilobytes | os.swap.cached | The amount of swap memory, in kilobytes, used as cache memory. |
| Free | Swap | Kilobytes | os.swap.free | The amount of swap memory free, in kilobytes. |
| In | Swap | Kilobytes | os.swap.in | The amount of memory, in kilobytes, swapped in from disk. |
| Out | Swap | Kilobytes | os.swap.out | The amount of memory, in kilobytes, swapped out to disk. |
| Total | Swap | Kilobytes | os.swap.total | The total amount of swap memory available in kilobytes. |
| Max Files | File Sys | Files | os.fileSys.maxFiles | The maximum number of files that can be created for the file system across all storage volumes. |
| Used Files | File Sys | Files | os.fileSys.usedFiles | The number of files in the file system across all storage volumes. |
| Used File Percent | File Sys | Files | os.fileSys.usedFilePercent | The percentage of available files in use across all storage volumes. |
| Used Percent | File Sys | Percentage | os.fileSys.usedPercent | The percentage of the file-system disk space in use across all storage volumes. |
| Used | File Sys | Kilobytes | os.fileSys.used | The amount of disk space used by files in the file system across all storage volumes, in kilobytes. |
| Total | File Sys | Kilobytes | os.fileSys.total | The total disk space available for the file system across all storage volumes, in kilobytes. |
| Max Files | File Sys | Files | os.fileSys..maxFiles | The maximum number of files that can be created for the storage volume. |
| Used Files | File Sys | Files | os.fileSys..usedFiles | The number of files in the storage volume. |
| Used File Percent | File Sys | Files | os.fileSys..usedFilePercent | The percentage of available files in use in the storage volume. |
| Used Percent | File Sys | Percentage | os.fileSys..usedPercent | The percentage of the storage volume disk space in use. |
| Used | File Sys | Kilobytes | os.fileSys..used | The amount of disk space used by files in the storage volume, in kilobytes. |
| Total | File Sys | Kilobytes | os.fileSys..total | The total disk space available in the storage volume, in kilobytes. |
| Rx | Network | Bytes per second | os.network.rx | The number of bytes received per second. |
| Tx | Network | Bytes per second | os.network.tx | The number of bytes uploaded per second. |
| Acu Utilization | General | Percentage | os.general.acuUtilization | The percentage of current capacity out of the maximum configured capacity. |
| Max Configured Acu | General | ACUs | os.general.maxConfiguredAcu | The maximum capacity configured by the user, in Aurora capacity units (ACUs). |
| Min Configured Acu | General | ACUs | os.general.minConfiguredAcu | The minimum capacity configured by the user, in ACUs. |
| Num VCPUs | General | vCPUs | os.general.numVCPUs | The number of virtual CPUs (vCPUs) for the DB instance. |
| Serverless Database Capacity | General | ACUs | os.general.serverlessDatabaseCapacity | The current capacity of the instance, in ACUs. |
## Performance Insights counters for Amazon RDS for MariaDB and MySQL
The following database counters are available with Performance Insights for Amazon RDS for MariaDB and MySQL.
**Topics**
+ [
### Native counters for RDS for MariaDB and RDS for MySQL
](#USER_PerfInsights_Counters.MySQL.Native)
+ [
### Non-native counters for Amazon RDS for MariaDB and MySQL
](#USER_PerfInsights_Counters.MySQL.NonNative)
### Native counters for RDS for MariaDB and RDS for MySQL
Native metrics are defined by the database engine and not by Amazon RDS. For definitions of these native metrics, see [Server Status Variables](https://dev.mysql.com/doc/refman/8.0/en/server-status-variables.html) (for 8.0) and [Server Status Variables](https://dev.mysql.com/doc/refman/8.4/en/server-status-variables.html) (for 8.4) in the MySQL documentation.
| Counter | Type | Unit | Metric |
| --- | --- | --- | --- |
| Com\$1analyze | SQL | Queries per second | db.SQL.Com\$1analyze |
| Com\$1optimize | SQL | Queries per second | db.SQL.Com\$1optimize |
| Com\$1select | SQL | Queries per second | db.SQL.Com\$1select |
| Connections | SQL | The number of connection attempts per minute (successful or not) to the MySQL server | db.Users.Connections |
| Innodb\$1rows\$1deleted | SQL | Rows per second | db.SQL.Innodb\$1rows\$1deleted |
| Innodb\$1rows\$1inserted | SQL | Rows per second | db.SQL.Innodb\$1rows\$1inserted |
| Innodb\$1rows\$1read | SQL | Rows per second | db.SQL.Innodb\$1rows\$1read |
| Innodb\$1rows\$1updated | SQL | Rows per second | db.SQL.Innodb\$1rows\$1updated |
| Select\$1full\$1join | SQL | Queries per second | db.SQL.Select\$1full\$1join |
| Select\$1full\$1range\$1join | SQL | Queries per second | db.SQL.Select\$1full\$1range\$1join |
| Select\$1range | SQL | Queries per second | db.SQL.Select\$1range |
| Select\$1range\$1check | SQL | Queries per second | db.SQL.Select\$1range\$1check |
| Select\$1scan | SQL | Queries per second | db.SQL.Select\$1scan |
| Slow\$1queries | SQL | Queries per second | db.SQL.Slow\$1queries |
| Sort\$1merge\$1passes | SQL | Queries per second | db.SQL.Sort\$1merge\$1passes |
| Sort\$1range | SQL | Queries per second | db.SQL.Sort\$1range |
| Sort\$1rows | SQL | Queries per second | db.SQL.Sort\$1rows |
| Sort\$1scan | SQL | Queries per second | db.SQL.Sort\$1scan |
| Questions | SQL | Queries per second | db.SQL.Questions |
| Innodb\$1row\$1lock\$1time | Locks | Milliseconds (average) | db.Locks.Innodb\$1row\$1lock\$1time |
| Table\$1locks\$1immediate | Locks | Requests per second | db.Locks.Table\$1locks\$1immediate |
| Table\$1locks\$1waited | Locks | Requests per second | db.Locks.Table\$1locks\$1waited |
| Aborted\$1clients | Users | Connections | db.Users.Aborted\$1clients |
| Aborted\$1connects | Users | Connections | db.Users.Aborted\$1connects |
| max\$1connections | Users | Connections | db.User.max\$1connections |
| Threads\$1created | Users | Connections | db.Users.Threads\$1created |
| Threads\$1running | Users | Connections | db.Users.Threads\$1running |
| Innodb\$1data\$1writes | I/O | Operations per second | db.IO.Innodb\$1data\$1writes |
| Innodb\$1dblwr\$1writes | I/O | Operations per second | db.IO.Innodb\$1dblwr\$1writes |
| Innodb\$1log\$1write\$1requests | I/O | Operations per second | db.IO.Innodb\$1log\$1write\$1requests |
| Innodb\$1log\$1writes | I/O | Operations per second | db.IO.Innodb\$1log\$1writes |
| Innodb\$1pages\$1written | I/O | Pages per second | db.IO.Innodb\$1pages\$1written |
| Created\$1tmp\$1disk\$1tables | Temp | Tables per second | db.Temp.Created\$1tmp\$1disk\$1tables |
| Created\$1tmp\$1tables | Temp | Tables per second | db.Temp.Created\$1tmp\$1tables |
| Innodb\$1buffer\$1pool\$1pages\$1data | Cache | Pages | db.Cache.Innodb\$1buffer\$1pool\$1pages\$1data |
| Innodb\$1buffer\$1pool\$1pages\$1total | Cache | Pages | db.Cache.Innodb\$1buffer\$1pool\$1pages\$1total |
| Innodb\$1buffer\$1pool\$1read\$1requests | Cache | Pages per second | db.Cache.Innodb\$1buffer\$1pool\$1read\$1requests |
| Innodb\$1buffer\$1pool\$1reads | Cache | Pages per second | db.Cache.Innodb\$1buffer\$1pool\$1reads |
| Opened\$1tables | Cache | Tables | db.Cache.Opened\$1tables |
| Opened\$1table\$1definitions | Cache | Tables | db.Cache.Opened\$1table\$1definitions |
| Qcache\$1hits | Cache | Queries | db.Cache.Qcache\$1hits |
### Non-native counters for Amazon RDS for MariaDB and MySQL
Non-native counter metrics are counters defined by Amazon RDS. A non-native metric can be a metric that you get with a specific query. A non-native metric also can be a derived metric, where two or more native counters are used in calculations for ratios, hit rates, or latencies.
| Counter | Type | Unit | Metric | Description | Definition |
| --- | --- | --- | --- | --- | --- |
| innodb\$1buffer\$1pool\$1hits | Cache | Reads | db.Cache.innoDB\$1buffer\$1pool\$1hits | The number of reads that InnoDB could satisfy from the buffer pool. | innodb\$1buffer\$1pool\$1read\$1requests - innodb\$1buffer\$1pool\$1reads |
| innodb\$1buffer\$1pool\$1hit\$1rate | Cache | Percentage | db.Cache.innoDB\$1buffer\$1pool\$1hit\$1rate | The percentage of reads that InnoDB could satisfy from the buffer pool. | 100 \$1 innodb\$1buffer\$1pool\$1read\$1requests / (innodb\$1buffer\$1pool\$1read\$1requests \$1 innodb\$1buffer\$1pool\$1reads) |
| innodb\$1buffer\$1pool\$1usage | Cache | Percentage | db.Cache.innoDB\$1buffer\$1pool\$1usage | The percentage of the InnoDB buffer pool that contains data (pages). When using compressed tables, this value can vary. For more information, see the information about `Innodb_buffer_pool_pages_data` and `Innodb_buffer_pool_pages_total` in [Server Status Variables](https://dev.mysql.com/doc/refman/8.0/en/server-status-variables.html) (for 8.0) and [Server Status Variables](https://dev.mysql.com/doc/refman/8.4/en/server-status-variables.html) (for 8.4) in the MySQL documentation. | Innodb\$1buffer\$1pool\$1pages\$1data / Innodb\$1buffer\$1pool\$1pages\$1total \$1 100.0 |
| query\$1cache\$1hit\$1rate | Cache | Percentage | db.Cache.query\$1cache\$1hit\$1rate | MySQL result set cache (query cache) hit ratio. | Qcache\$1hits / (QCache\$1hits \$1 Com\$1select) \$1 100 |
| innodb\$1datafile\$1writes\$1to\$1disk | I/O | Writes | db.IO.innoDB\$1datafile\$1writes\$1to\$1disk | The number of InnoDB data file writes to disk, excluding double write and redo logging write operations. | Innodb\$1data\$1writes - Innodb\$1log\$1writes - Innodb\$1dblwr\$1writes |
| innodb\$1rows\$1changed | SQL | Rows | db.SQL.innodb\$1rows\$1changed | The total InnoDB row operations. | db.SQL.Innodb\$1rows\$1inserted \$1 db.SQL.Innodb\$1rows\$1deleted \$1 db.SQL.Innodb\$1rows\$1updated |
| active\$1transactions | Transactions | Transactions | db.Transactions.active\$1transactions | The total active transactions. | SELECT COUNT(1) AS active\$1transactions FROM INFORMATION\$1SCHEMA.INNODB\$1TRX |
| trx\$1rseg\$1history\$1len | Transactions | None | db.Transactions.trx\$1rseg\$1history\$1len | A list of the undo log pages for committed transactions that is maintained by the InnoDB transaction system to implement multi-version concurrency control. For more information about undo log records details, see [InnoDB Multi-Versioning](https://dev.mysql.com/doc/refman/8.0/en/innodb-multi-versioning.html) (for 8.0) and [InnoDB Multi-Versioning](https://dev.mysql.com/doc/refman/8.4/en/innodb-multi-versioning.html) (for 8.4) in the MySQL documentation. | SELECT COUNT AS trx\$1rseg\$1history\$1len FROM INFORMATION\$1SCHEMA.INNODB\$1METRICS WHERE NAME='trx\$1rseg\$1history\$1len' |
| innodb\$1deadlocks | Locks | Locks | db.Locks.innodb\$1deadlocks | The total number of deadlocks. | SELECT COUNT AS innodb\$1deadlocks FROM INFORMATION\$1SCHEMA.INNODB\$1METRICS WHERE NAME='lock\$1deadlocks' |
| innodb\$1lock\$1timeouts | Locks | Locks | db.Locks.innodb\$1lock\$1timeouts | The total number of locks that timed out. | SELECT COUNT AS innodb\$1lock\$1timeouts FROM INFORMATION\$1SCHEMA.INNODB\$1METRICS WHERE NAME='lock\$1timeouts' |
| innodb\$1row\$1lock\$1waits | Locks | Locks | db.Locks.innodb\$1row\$1lock\$1waits | The total number of row locks that resulted in a wait. | SELECT COUNT AS innodb\$1row\$1lock\$1waits FROM INFORMATION\$1SCHEMA.INNODB\$1METRICS WHERE NAME='lock\$1row\$1lock\$1waits' |
## Performance Insights counters for Amazon RDS for Microsoft SQL Server
The following database counters are available with Performance Insights for RDS for Microsoft SQL Server.
### Native counters for RDS for Microsoft SQL Server
Native metrics are defined by the database engine and not by Amazon RDS. You can find definitions for these native metrics in [Use SQL Server Objects](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/use-sql-server-objects?view=sql-server-2017) in the Microsoft SQL Server documentation.
| Counter | Type | Unit | Metric |
| --- | --- | --- | --- |
| Forwarded Records | [Access Methods](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-access-methods-object?view=sql-server-2017) | Records per second | db.Access Methods.Forwarded Records |
| Page Splits | [Access Methods](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-access-methods-object?view=sql-server-2017) | Splits per second | db.Access Methods.Page Splits |
| Buffer cache hit ratio | [Buffer Manager](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-buffer-manager-object?view=sql-server-2017) | Ratio | db.Buffer Manager.Buffer cache hit ratio |
| Page life expectancy | [Buffer Manager](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-buffer-manager-object?view=sql-server-2017) | Expectancy in seconds | db.Buffer Manager.Page life expectancy |
| Page lookups | [Buffer Manager](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-buffer-manager-object?view=sql-server-2017) | Lookups per second | db.Buffer Manager.Page lookups |
| Page reads | [Buffer Manager](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-buffer-manager-object?view=sql-server-2017) | Reads per second | db.Buffer Manager.Page reads |
| Page writes | [Buffer Manager](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-buffer-manager-object?view=sql-server-2017) | Writes per second | db.Buffer Manager.Page writes |
| Active Transactions | [Databases](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-databases-object?view=sql-server-2017) | Transactions | db.Databases.Active Transactions (\$1Total) |
| Log Bytes Flushed | [Databases](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-databases-object?view=sql-server-2017) | Bytes flushed per second | db.Databases.Log Bytes Flushed (\$1Total) |
| Log Flush Waits | [Databases](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-databases-object?view=sql-server-2017) | Waits per second | db.Databases.Log Flush Waits (\$1Total) |
| Log Flushes | [Databases](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-databases-object?view=sql-server-2017) | Flushes per second | db.Databases.Log Flushes (\$1Total) |
| Write Transactions | [Databases](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-databases-object?view=sql-server-2017) | Transactions per second | db.Databases.Write Transactions (\$1Total) |
| Processes blocked | [General Statistics](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-general-statistics-object?view=sql-server-2017) | Processes blocked | db.General Statistics.Processes blocked |
| User Connections | [General Statistics](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-general-statistics-object?view=sql-server-2017) | Connections | db.General Statistics.User Connections |
| Latch Waits | [Latches](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-latches-object?view=sql-server-2017) | Waits per second | db.Latches.Latch Waits |
| Number of Deadlocks | [Locks](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-locks-object?view=sql-server-2017) | Deadlocks per second | db.Locks.Number of Deadlocks (\$1Total) |
| Memory Grants Pending | [Memory Manager](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-memory-manager-object?view=sql-server-2017) | Memory grants | db.Memory Manager.Memory Grants Pending |
| Batch Requests | [SQL Statistics](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-sql-statistics-object?view=sql-server-2017) | Requests per second | db.SQL Statistics.Batch Requests |
| SQL Compilations | [SQL Statistics](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-sql-statistics-object?view=sql-server-2017) | Compilations per second | db.SQL Statistics.SQL Compilations |
| SQL Re-Compilations | [SQL Statistics](https://docs.microsoft.com/en-us/sql/relational-databases/performance-monitor/sql-server-sql-statistics-object?view=sql-server-2017) | Re-compilations per second | db.SQL Statistics.SQL Re-Compilations |
## Performance Insights counters for Amazon RDS for Oracle
The following database counters are available with Performance Insights for RDS for Oracle.
### Native counters for RDS for Oracle
Native metrics are defined by the database engine and not by Amazon RDS. You can find definitions for these native metrics in [Statistics Descriptions](https://docs.oracle.com/en/database/oracle/oracle-database/12.2/refrn/statistics-descriptions-2.html#GUID-2FBC1B7E-9123-41DD-8178-96176260A639) in the Oracle documentation.
**Note**
For the `CPU used by this session` counter metric, the unit has been transformed from the native centiseconds to active sessions to make the value easier to use. For example, CPU send in the DB Load chart represents the demand for CPU. The counter metric `CPU used by this session` represents the amount of CPU used by Oracle sessions. You can compare CPU send to the `CPU used by this session` counter metric. When demand for CPU is higher than CPU used, sessions are waiting for CPU time.
| Counter | Type | Unit | Metric |
| --- | --- | --- | --- |
| CPU used by this session | User | Active sessions | db.User.CPU used by this session |
| SQL\$1Net roundtrips to/from client | User | Roundtrips per second | db.User.SQL\$1Net roundtrips to/from client |
| Bytes received via SQL\$1Net from client | User | Bytes per second | db.User.bytes received via SQL\$1Net from client |
| User commits | User | Commits per second | db.User.user commits |
| Logons cumulative | User | Logons per second | db.User.logons cumulative |
| User calls | User | Calls per second | db.User.user calls |
| Bytes sent via SQL\$1Net to client | User | Bytes per second | db.User.bytes sent via SQL\$1Net to client |
| User rollbacks | User | Rollbacks per second | db.User.user rollbacks |
| Redo size | Redo | Bytes per second | db.Redo.redo size |
| Parse count (total) | SQL | Parses per second | db.SQL.parse count (total) |
| Parse count (hard) | SQL | Parses per second | db.SQL.parse count (hard) |
| Table scan rows gotten | SQL | Rows per second | db.SQL.table scan rows gotten |
| Sorts (memory) | SQL | Sorts per second | db.SQL.sorts (memory) |
| Sorts (disk) | SQL | Sorts per second | db.SQL.sorts (disk) |
| Sorts (rows) | SQL | Sorts per second | db.SQL.sorts (rows) |
| Physical read bytes | Cache | Bytes per second | db.Cache.physical read bytes |
| DB block gets | Cache | Blocks per second | db.Cache.db block gets |
| DBWR checkpoints | Cache | Checkpoints per minute | db.Cache.DBWR checkpoints |
| Physical reads | Cache | Reads per second | db.Cache.physical reads |
| Consistent gets from cache | Cache | Gets per second | db.Cache.consistent gets from cache |
| DB block gets from cache | Cache | Gets per second | db.Cache.db block gets from cache |
| Consistent gets | Cache | Gets per second | db.Cache.consistent gets |
## Performance Insights counters for Amazon RDS for PostgreSQL
The following database counters are available with Performance Insights for Amazon RDS for PostgreSQL.
**Topics**
+ [
### Native counters for Amazon RDS for PostgreSQL
](#USER_PerfInsights_Counters.PostgreSQL.Native)
+ [
### Non-native counters for Amazon RDS for PostgreSQL
](#USER_PerfInsights_Counters.PostgreSQL.NonNative)
### Native counters for Amazon RDS for PostgreSQL
Native metrics are defined by the database engine and not by Amazon RDS. You can find definitions for these native metrics in [Viewing Statistics](https://www.postgresql.org/docs/current/monitoring-stats.html#MONITORING-STATS-VIEWS) in the PostgreSQL documentation.
| Counter | Type | Unit | Metric |
| --- | --- | --- | --- |
| blks\$1hit | Cache | Blocks per second | db.Cache.blks\$1hit |
| buffers\$1alloc | Cache | Blocks per second | db.Cache.buffers\$1alloc |
| buffers\$1checkpoint | Checkpoint | Blocks per second | db.Checkpoint.buffers\$1checkpoint |
| checkpoint\$1sync\$1time | Checkpoint | Milliseconds per checkpoint | db.Checkpoint.checkpoint\$1sync\$1time |
| checkpoint\$1write\$1time | Checkpoint | Milliseconds per checkpoint | db.Checkpoint.checkpoint\$1write\$1time |
| checkpoints\$1req | Checkpoint | Checkpoints per minute | db.Checkpoint.checkpoints\$1req |
| checkpoints\$1timed | Checkpoint | Checkpoints per minute | db.Checkpoint.checkpoints\$1timed |
| maxwritten\$1clean | Checkpoint | Bgwriter clean stops per minute | db.Checkpoint.maxwritten\$1clean |
| deadlocks | Concurrency | Deadlocks per minute | db.Concurrency.deadlocks |
| blk\$1read\$1time | I/O | Milliseconds | db.IO.blk\$1read\$1time |
| blks\$1read | I/O | Blocks per second | db.IO.blks\$1read |
| buffers\$1backend | I/O | Blocks per second | db.IO.buffers\$1backend |
| buffers\$1backend\$1fsync | I/O | Blocks per second | db.IO.buffers\$1backend\$1fsync |
| buffers\$1clean | I/O | Blocks per second | db.IO.buffers\$1clean |
| tup\$1deleted | SQL | Tuples per second | db.SQL.tup\$1deleted |
| tup\$1fetched | SQL | Tuples per second | db.SQL.tup\$1fetched |
| tup\$1inserted | SQL | Tuples per second | db.SQL.tup\$1inserted |
| tup\$1returned | SQL | Tuples per second | db.SQL.tup\$1returned |
| tup\$1updated | SQL | Tuples per second | db.SQL.tup\$1updated |
| temp\$1bytes | Temp | Bytes per second | db.Temp.temp\$1bytes |
| temp\$1files | Temp | Files per minute | db.Temp.temp\$1files |
| xact\$1commit | Transactions | Commits per second | db.Transactions.xact\$1commit |
| xact\$1rollback | Transactions | Rollbacks per second | db.Transactions.xact\$1rollback |
| numbackends | User | Connections | db.User.numbackends |
| archived\$1count | Write-ahead log (WAL) | Files per minute | db.WAL.archived\$1count |
### Non-native counters for Amazon RDS for PostgreSQL
Non-native counter metrics are counters defined by Amazon RDS. A non-native metric can be a metric that you get with a specific query. A non-native metric also can be a derived metric, where two or more native counters are used in calculations for ratios, hit rates, or latencies.
| Counter | Type | Unit | Metric | Description | Definition |
| --- | --- | --- | --- | --- | --- |
| checkpoint\$1sync\$1latency | Checkpoint | db.Checkpoint.checkpoint\$1sync\$1latency | | The total amount of time that has been spent in the portion of checkpoint processing where files are synchronized to disk. | checkpoint\$1sync\$1time / (checkpoints\$1timed \$1 checkpoints\$1req) |
| checkpoint\$1write\$1latency | Checkpoint | db.Checkpoint.checkpoint\$1write\$1latency | The total amount of time that has been spent in the portion of checkpoint processing where files are written to disk. | checkpoint\$1write\$1time / (checkpoints\$1timed \$1 checkpoints\$1req) |
| read\$1latency | I/O | db.IO.read\$1latency | The time spent reading data file blocks by backends in this instance. | blk\$1read\$1time / blks\$1read |
| idle\$1in\$1transaction\$1aborted\$1count | State | Sessions | db.state.idle\$1in\$1transaction\$1aborted\$1count | The number of sessions in the idle in transaction (aborted) state. | Not applicable |
| idle\$1in\$1transaction\$1count | State | Sessions | db.state.idle\$1in\$1transaction\$1count | The number of sessions in the idle in transaction state. | Not applicable |
| idle\$1in\$1transaction\$1max\$1time | State | Seconds | db.state.idle\$1in\$1transaction\$1max\$1time | The duration of the longest running transaction in the idle in transaction state, in seconds. | Not applicable |
| active\$1transactions | Transactions | Transactions | db.Transactions.active\$1transactions | The number of active transactions. | Not applicable |
| blocked\$1transactions | Transactions | Transactions | db.Transactions.blocked\$1transactions | The number of blocked transactions. | Not applicable |
| oldest\$1active\$1logical\$1replication\$1slot\$1xid\$1age | Transactions | db.Transactions.oldest\$1active\$1logical\$1replication\$1slot\$1xid\$1age | The age of the oldest transaction in an active logical replication slot. For more information, see [Logical replication slot](Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Resolving_Identifiableblockers.md#Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Logical_replication_slot). | – |
| oldest\$1inactive\$1logical\$1replication\$1slot\$1xid\$1age | Transactions | db.Transactions.oldest\$1inactive\$1logical\$1replication\$1slot\$1xid\$1age | The age of the oldest transaction in an inactive logical replication slot. For more information, see [Logical replication slot](Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Resolving_Identifiableblockers.md#Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Logical_replication_slot). | – |
| oldest\$1prepared\$1transaction\$1xid\$1age | Transactions | db.Transactions.oldest\$1prepared\$1transaction\$1xid\$1age | The age of the oldest prepared transaction. For more information, see [Prepared transaction](Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Resolving_Identifiableblockers.md#Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Prepared_transaction). | – |
| oldest\$1running\$1transaction\$1xid\$1age | Transactions | db.Transactions.oldest\$1running\$1transaction\$1xid\$1age | The age of the oldest running transaction. For more information, see [Active statement](Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Resolving_Identifiableblockers.md#Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Active_statement) for the oldest running active transaction and [Idle in transaction](Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Resolving_Identifiableblockers.md#Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Idle_in_transaction) for the oldest running idle-in-transaction. | – |
| oldest\$1hot\$1standby\$1feedback\$1xid\$1age | Transactions | db.Transactions.oldest\$1hot\$1standby\$1feedback\$1xid\$1age | The age of the oldest running transaction on a read replica with `hot_standby_feedback` enabled. For more information, see [Read replicas](Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Resolving_Identifiableblockers.md#Appendix.PostgreSQL.CommonDBATasks.Autovacuum_Monitoring.Read_replicas). | – |
| max\$1used\$1xact\$1ids | Transactions | Transactions | db.Transactions.max\$1used\$1xact\$1ids | The number of transactions that haven't been vacuumed. | Not applicable |
| max\$1connections | Users | Connections | db.User.max\$1connections | The maximum number of connections allowed for a DB instance as configured in max\$1connections parameter. | Not applicable |
| archive\$1failed\$1count | WAL | Files per minute | db.WAL.archive\$1failed\$1count | The number of failed attempts for archiving WAL files, in files per minute. | Not applicable |
# SQL statistics for Performance Insights
*SQL statistics* are performance-related metrics about SQL queries that are collected by Performance Insights. Performance Insights gathers statistics for each second that a query is running and for each SQL call. The SQL statistics are an average for the selected time range.
A SQL digest is a composite of all queries having a given pattern but not necessarily having the same literal values. The digest replaces literal values with a question mark. For example, `SELECT * FROM emp WHERE lname= ?`. This digest might consist of the following child queries:
```
SELECT * FROM emp WHERE lname = 'Sanchez'
SELECT * FROM emp WHERE lname = 'Olagappan'
SELECT * FROM emp WHERE lname = 'Wu'
```
All engines support SQL statistics for digest queries.
For the region, DB engine, and instance class support information for this feature, see [Amazon RDS DB engine, Region, and instance class support for Performance Insights features](USER_PerfInsights.Overview.Engines.md#USER_PerfInsights.Overview.PIfeatureEngnRegSupport)
**Topics**
+ [
# SQL statistics for MariaDB and MySQL
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.MySQL.md)
+ [
# SQL statistics for Amazon RDS for Oracle
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.Oracle.md)
+ [
# SQL statistics for Amazon RDS for SQL Server
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.SQLServer.md)
+ [
# SQL statistics for RDS PostgreSQL
](USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.PostgreSQL.md)
# SQL statistics for MariaDB and MySQL
MariaDB and MySQL collect SQL statistics only at the digest level. No statistics are shown at the statement level.
**Topics**
+ [
## Digest statistics for MariaDB and MySQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.MySQL.truncation)
+ [
## Per-second statistics for MariaDB and MySQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.MySQL.per-second)
+ [
## Per-call statistics for MariaDB and MySQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.MySQL.truncation.per-call)
+ [
## Primary statistics for MariaDB and MySQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.MySQL.primary)
## Digest statistics for MariaDB and MySQL
Performance Insights collects SQL digest statistics from the `events_statements_summary_by_digest` table. The `events_statements_summary_by_digest` table is managed by your database.
The digest table doesn't have an eviction policy. When the table is full, the AWS Management Console shows the following message:
```
Performance Insights is unable to collect SQL Digest statistics on new queries because the table events_statements_summary_by_digest is full.
Please truncate events_statements_summary_by_digest table to clear the issue. Check the User Guide for more details.
```
In this situation, MariaDB and MySQL don't track SQL queries. To address this issue, Performance Insights automatically truncates the digest table when both of the following conditions are met:
+ The table is full.
+ Performance Insights manages the Performance Schema automatically.
For automatic management, the `performance_schema` parameter must be set to `0` and the **Source** must not be set to `user`. If Performance Insights isn't managing the Performance Schema automatically, see [Overview of the Performance Schema for Performance Insights on Amazon RDS for MariaDB or MySQL](USER_PerfInsights.EnableMySQL.md).
In the AWS CLI, check the source of a parameter value by running the [describe-db-parameters](https://docs.aws.amazon.com/cli/latest/reference/rds/describe-db-parameters.html) command.
## Per-second statistics for MariaDB and MySQL
The following SQL statistics are available for MariaDB and MySQL DB instances.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.count\$1star\$1per\$1sec | Calls per second |
| db.sql\$1tokenized.stats.sum\$1timer\$1wait\$1per\$1sec | Average latency per second (in ms) |
| db.sql\$1tokenized.stats.sum\$1select\$1full\$1join\$1per\$1sec | Select full join per second |
| db.sql\$1tokenized.stats.sum\$1select\$1range\$1check\$1per\$1sec | Select range check per second |
| db.sql\$1tokenized.stats.sum\$1select\$1scan\$1per\$1sec | Select scan per second |
| db.sql\$1tokenized.stats.sum\$1sort\$1merge\$1passes\$1per\$1sec | Sort merge passes per second |
| db.sql\$1tokenized.stats.sum\$1sort\$1scan\$1per\$1sec | Sort scans per second |
| db.sql\$1tokenized.stats.sum\$1sort\$1range\$1per\$1sec | Sort ranges per second |
| db.sql\$1tokenized.stats.sum\$1sort\$1rows\$1per\$1sec | Sort rows per second |
| db.sql\$1tokenized.stats.sum\$1rows\$1affected\$1per\$1sec | Rows affected per second |
| db.sql\$1tokenized.stats.sum\$1rows\$1examined\$1per\$1sec | Rows examined per second |
| db.sql\$1tokenized.stats.sum\$1rows\$1sent\$1per\$1sec | Rows sent per second |
| db.sql\$1tokenized.stats.sum\$1created\$1tmp\$1disk\$1tables\$1per\$1sec | Created temporary disk tables per second |
| db.sql\$1tokenized.stats.sum\$1created\$1tmp\$1tables\$1per\$1sec | Created temporary tables per second |
| db.sql\$1tokenized.stats.sum\$1lock\$1time\$1per\$1sec | Lock time per second (in ms) |
## Per-call statistics for MariaDB and MySQL
The following metrics provide per call statistics for a SQL statement.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.sum\$1timer\$1wait\$1per\$1call | Average latency per call (in ms) |
| db.sql\$1tokenized.stats.sum\$1select\$1full\$1join\$1per\$1call | Select full joins per call |
| db.sql\$1tokenized.stats.sum\$1select\$1range\$1check\$1per\$1call | Select range check per call |
| db.sql\$1tokenized.stats.sum\$1select\$1scan\$1per\$1call | Select scans per call |
| db.sql\$1tokenized.stats.sum\$1sort\$1merge\$1passes\$1per\$1call | Sort merge passes per call |
| db.sql\$1tokenized.stats.sum\$1sort\$1scan\$1per\$1call | Sort scans per call |
| db.sql\$1tokenized.stats.sum\$1sort\$1range\$1per\$1call | Sort ranges per call |
| db.sql\$1tokenized.stats.sum\$1sort\$1rows\$1per\$1call | Sort rows per call |
| db.sql\$1tokenized.stats.sum\$1rows\$1affected\$1per\$1call | Rows affected per call |
| db.sql\$1tokenized.stats.sum\$1rows\$1examined\$1per\$1call | Rows examined per call |
| db.sql\$1tokenized.stats.sum\$1rows\$1sent\$1per\$1call | Rows sent per call |
| db.sql\$1tokenized.stats.sum\$1created\$1tmp\$1disk\$1tables\$1per\$1call | Created temporary disk tables per call |
| db.sql\$1tokenized.stats.sum\$1created\$1tmp\$1tables\$1per\$1call | Created temporary tables per call |
| db.sql\$1tokenized.stats.sum\$1lock\$1time\$1per\$1call | Lock time per call (in ms) |
## Primary statistics for MariaDB and MySQL
The following SQL statistics are available for MariaDB and MySQL DB instances.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.count\$1star | Calls |
| db.sql\$1tokenized.stats.sum\$1timer\$1wait | Wait time (in ms) |
| db.sql\$1tokenized.stats.sum\$1select\$1full\$1join | Select full join |
| db.sql\$1tokenized.stats.sum\$1select\$1range\$1check | Select range checks |
| db.sql\$1tokenized.stats.sum\$1select\$1scan | Select scans |
| db.sql\$1tokenized.stats.sum\$1sort\$1merge\$1passes | Sort merge passes |
| db.sql\$1tokenized.stats.sum\$1sort\$1scan | Sort scans |
| db.sql\$1tokenized.stats.sum\$1sort\$1range | Sort ranges |
| db.sql\$1tokenized.stats.sum\$1sort\$1rows | Sort rows |
| db.sql\$1tokenized.stats.sum\$1rows\$1affected | Rows affected |
| db.sql\$1tokenized.stats.sum\$1rows\$1examined | Rows examined |
| db.sql\$1tokenized.stats.sum\$1rows\$1sent | Rows sent |
| db.sql\$1tokenized.stats.sum\$1created\$1tmp\$1disk\$1tables | Created temporary disk tables |
| db.sql\$1tokenized.stats.sum\$1created\$1tmp\$1tables | Created temporary tables |
| db.sql\$1tokenized.stats.sum\$1lock\$1time | Lock time (in ms) |
# SQL statistics for Amazon RDS for Oracle
Amazon RDS for Oracle collects SQL statistics both at the statement and digest level. At the statement level, the ID column represents the value of `V$SQL.SQL_ID`. At the digest level, the ID column shows the value of `V$SQL.FORCE_MATCHING_SIGNATURE`.
If the ID is `0` at the digest level, Oracle Database has determined that this statement is not suitable for reuse. In this case, the child SQL statements could belong to different digests. However, the statements are grouped together under the `digest_text` for the first SQL statement collected.
**Topics**
+ [
## Per-second statistics for Oracle
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.Oracle.per-second)
+ [
## Per-call statistics for Oracle
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.Oracle.per-call)
+ [
## Primary statistics for Oracle
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.Oracle.primary)
## Per-second statistics for Oracle
The following metrics provide per-second statistics for an Oracle SQL query.
| Metric | Unit |
| --- | --- |
| db.sql.stats.executions\$1per\$1sec | Number of executions per second |
| db.sql.stats.elapsed\$1time\$1per\$1sec | Average active executions (AAE) |
| db.sql.stats.rows\$1processed\$1per\$1sec | Rows processed per second |
| db.sql.stats.buffer\$1gets\$1per\$1sec | Buffer gets per second |
| db.sql.stats.physical\$1read\$1requests\$1per\$1sec | Physical reads per second |
| db.sql.stats.physical\$1write\$1requests\$1per\$1sec | Physical writes per second |
| db.sql.stats.total\$1sharable\$1mem\$1per\$1sec | Total shareable memory per second (in bytes) |
| db.sql.stats.cpu\$1time\$1per\$1sec | CPU time per second (in ms) |
The following metrics provide per-second statistics for an Oracle SQL digest query.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.executions\$1per\$1sec | Number of executions per second |
| db.sql\$1tokenized.stats.elapsed\$1time\$1per\$1sec | Average active executions (AAE) |
| db.sql\$1tokenized.stats.rows\$1processed\$1per\$1sec | Rows processed per second |
| db.sql\$1tokenized.stats.buffer\$1gets\$1per\$1sec | Buffer gets per second |
| db.sql\$1tokenized.stats.physical\$1read\$1requests\$1per\$1sec | Physical reads per second |
| db.sql\$1tokenized.stats.physical\$1write\$1requests\$1per\$1sec | Physical writes per second |
| db.sql\$1tokenized.stats.total\$1sharable\$1mem\$1per\$1sec | Total shareable memory per second (in bytes) |
| db.sql\$1tokenized.stats.cpu\$1time\$1per\$1sec | CPU time per second (in ms) |
## Per-call statistics for Oracle
The following metrics provide per-call statistics for an Oracle SQL statement.
| Metric | Unit |
| --- | --- |
| db.sql.stats.elapsed\$1time\$1per\$1exec | Elapsed time per executions (in ms) |
| db.sql.stats.rows\$1processed\$1per\$1exec | Rows processed per execution |
| db.sql.stats.buffer\$1gets\$1per\$1exec | Buffer gets per execution |
| db.sql.stats.physical\$1read\$1requests\$1per\$1exec | Physical reads per execution |
| db.sql.stats.physical\$1write\$1requests\$1per\$1exec | Physical writes per execution |
| db.sql.stats.total\$1sharable\$1mem\$1per\$1exec | Total shareable memory per execution (in bytes) |
| db.sql.stats.cpu\$1time\$1per\$1exec | CPU time per execution (in ms) |
The following metrics provide per-call statistics for an Oracle SQL digest query.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.elapsed\$1time\$1per\$1exec | Elapsed time per executions (in ms) |
| db.sql\$1tokenized.stats.rows\$1processed\$1per\$1exec | Rows processed per execution |
| db.sql\$1tokenized.stats.buffer\$1gets\$1per\$1exec | Buffer gets per execution |
| db.sql\$1tokenized.stats.physical\$1read\$1requests\$1per\$1exec | Physical reads per execution |
| db.sql\$1tokenized.stats.physical\$1write\$1requests\$1per\$1exec | Physical writes per execution |
| db.sql\$1tokenized.stats.total\$1sharable\$1mem\$1per\$1exec | Total shareable memory per execution (in bytes) |
| db.sql\$1tokenized.stats.cpu\$1time\$1per\$1exec | CPU time per execution (in ms) |
## Primary statistics for Oracle
The following metrics provide primary statistics for an Oracle SQL query.
| Metric | Unit |
| --- | --- |
| db.sql.stats.executions | Number of executions |
| db.sql.stats.elapsed\$1time | Elapsed time (in ms) |
| db.sql.stats.rows\$1processed | Rows processed |
| db.sql.stats.buffer\$1gets | Buffer gets |
| db.sql.stats.physical\$1read\$1requests | Physical reads |
| db.sql.stats.physical\$1write\$1requests | Physical writes |
| db.sql.stats.total\$1sharable\$1mem | Total shareable memory (in bytes) |
| db.sql.stats.cpu\$1time | CPU time (in ms) |
The following metrics provide primary statistics for an Oracle SQL digest query.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.executions | Number of executions |
| db.sql\$1tokenized.stats.elapsed\$1time | Elapsed time (in ms) |
| db.sql\$1tokenized.stats.rows\$1processed | Rows processed |
| db.sql\$1tokenized.stats.buffer\$1gets | Buffer gets |
| db.sql\$1tokenized.stats.physical\$1read\$1requests | Physical reads |
| db.sql\$1tokenized.stats.physical\$1write\$1requests | Physical writes |
| db.sql\$1tokenized.stats.total\$1sharable\$1mem | Total shareable memory (in bytes) |
| db.sql\$1tokenized.stats.cpu\$1time | CPU time (in ms) |
# SQL statistics for Amazon RDS for SQL Server
Amazon RDS for SQL Server collects SQL statistics both at the statement and digest level. At the statement level, the ID column represents the value of `sql_handle`. At the digest level, the ID column shows the value of `query_hash`.
SQL Server returns NULL values for `query_hash` for a few statements. For example, ALTER INDEX, CHECKPOINT, UPDATE STATISTICS, COMMIT TRANSACTION, FETCH NEXT FROM Cursor, and a few INSERT statements, SELECT @, conditional statements, and executable stored procedures. In this case, the `sql_handle` value is displayed as the ID at the digest level for that statement.
**Topics**
+ [
## Per-second statistics for SQL Server
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.SQLServer.per-second)
+ [
## Per-call statistics for SQL Server
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.SQLServer.per-call)
+ [
## Primary statistics for SQL Server
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.SQLServer.primary)
## Per-second statistics for SQL Server
The following metrics provide per-second statistics for a SQL Server SQL query.
| Metric | Unit |
| --- | --- |
| db.sql.stats.execution\$1count\$1per\$1sec | Number of executions per second |
| db.sql.stats.total\$1elapsed\$1time\$1per\$1sec | Total elapsed time per second |
| db.sql.stats.total\$1rows\$1per\$1sec | Total rows processed per second |
| db.sql.stats.total\$1logical\$1reads\$1per\$1sec | Total logical reads per second |
| db.sql.stats.total\$1logical\$1writes\$1per\$1sec | Total logical writes per second |
| db.sql.stats.total\$1physical\$1reads\$1per\$1sec | Total physical reads per second |
| db.sql.stats.total\$1worker\$1time\$1per\$1sec | Total CPU time (in ms) |
The following metrics provide per-second statistics for a SQL Server SQL digest query.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.execution\$1count\$1per\$1sec | Number of execution per second |
| db.sql\$1tokenized.stats.total\$1elapsed\$1time\$1per\$1sec | Total elapsed time per second |
| db.sql\$1tokenized.stats.total\$1rows\$1per\$1sec | Total rows processed per second |
| db.sql\$1tokenized.stats.total\$1logical\$1reads\$1per\$1sec | Total logical reads per second |
| db.sql\$1tokenized.stats.total\$1logical\$1writes\$1per\$1sec | Total logical writes per second |
| db.sql\$1tokenized.stats.total\$1physical\$1reads\$1per\$1sec | Total physical reads per second |
| db.sql\$1tokenized.stats.total\$1worker\$1time\$1per\$1sec | Total CPU time (in ms) |
## Per-call statistics for SQL Server
The following metrics provide per-call statistics for a SQL Server SQL statement.
| Metric | Unit |
| --- | --- |
| db.sql.stats.total\$1elapsed\$1time\$1per\$1call | Total elapsed time per execution (in ms) |
| db.sql.stats.total\$1rows\$1per\$1call | Total rows processed per execution |
| db.sql.stats.total\$1logical\$1reads\$1per\$1call | Total logical reads per execution |
| db.sql.stats.total\$1logical\$1writes\$1per\$1call | Total logical writes per execution |
| db.sql.stats.total\$1physical\$1reads\$1per\$1call | Total physical reads per execution |
| db.sql.stats.total\$1worker\$1time\$1per\$1call | Total CPU time per execution (in ms) |
The following metrics provide per-call statistics for a SQL Server SQL digest query.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.total\$1elapsed\$1time\$1per\$1call | Total elapsed time per execution |
| db.sql\$1tokenized.stats.total\$1rows\$1per\$1call | Total rows processed per execution |
| db.sql\$1tokenized.stats.total\$1logical\$1reads\$1per\$1call | Total logical reads per execution |
| db.sql\$1tokenized.stats.total\$1logical\$1writes\$1per\$1call | Total logical writes per execution |
| db.sql\$1tokenized.stats.total\$1physical\$1reads\$1per\$1call | Total physical reads per execution |
| db.sql\$1tokenized.stats.total\$1worker\$1time\$1per\$1call | Total CPU time per execution (in ms) |
## Primary statistics for SQL Server
The following metrics provide primary statistics for a SQL Server SQL query.
| Metric | Unit |
| --- | --- |
| db.sql.stats.execution\$1count | Number of executions |
| db.sql.stats.total\$1elapsed\$1time | Total elapsed time (in ms) |
| db.sql.stats.total\$1rows | Total rows processed |
| db.sql.stats.total\$1logical\$1reads | Total logical reads |
| db.sql.stats.total\$1logical\$1writes | Total logical writes |
| db.sql.stats.total\$1physical\$1reads | Total physical reads |
| db.sql.stats.total\$1worker\$1time | Total CPU time (in ms) |
The following metrics provide primary statistics for a SQL Server SQL digest query.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.execution\$1count | Number of execution |
| db.sql\$1tokenized.stats.total\$1elapsed\$1time | Total elapsed time (in ms) |
| db.sql\$1tokenized.stats.total\$1rows | Total rows processed |
| db.sql\$1tokenized.stats.total\$1logical\$1reads | Total logical reads |
| db.sql\$1tokenized.stats.total\$1logical\$1writes | Total logical writes |
| db.sql\$1tokenized.stats.total\$1physical\$1reads | Total physical reads |
| db.sql\$1tokenized.stats.total\$1worker\$1time | Total CPU time (in ms) |
# SQL statistics for RDS PostgreSQL
For each SQL call and for each second that a query runs, Performance Insights collects SQL statistics. RDS for PostgreSQL collect SQL statistics only at the digest–level. No statistics are shown at the statement-level.
Following, you can find information about digest-level statistics for RDS for PostgreSQL.
**Topics**
+ [
## Digest statistics for RDS PostgreSQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.PostgreSQL.digest)
+ [
## Per-second digest statistics for RDS PostgreSQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.PostgreSQL.per-second)
+ [
## Per-call digest statistics for RDS PostgreSQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.PostgreSQL.per-call)
+ [
## Primary statistics for RDS PostgreSQL
](#USER_PerfInsights.UsingDashboard.AnalyzeDBLoad.AdditionalMetrics.PostgreSQL.primary)
## Digest statistics for RDS PostgreSQL
To view SQL digest statistics, RDS PostgreSQL must load the `pg_stat_statements` library. For PostgreSQL DB instances that are compatible with PostgreSQL 11 or later, the database loads this library by default. For PostgreSQL DB instances that are compatible with PostgreSQL 10 or earlier, enable this library manually. To enable it manually, add `pg_stat_statements` to `shared_preload_libraries` in the DB parameter group associated with the DB instance. Then reboot your DB instance. For more information, see [Parameter groups for Amazon RDS](USER_WorkingWithParamGroups.md).
**Note**
Performance Insights can only collect statistics for queries in `pg_stat_activity` that aren't truncated. By default, PostgreSQL databases truncate queries longer than 1,024 bytes. To increase the query size, change the `track_activity_query_size` parameter in the DB parameter group associated with your DB instance. When you change this parameter, a DB instance reboot is required.
## Per-second digest statistics for RDS PostgreSQL
The following SQL digest statistics are available for PostgreSQL DB instances.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.calls\$1per\$1sec | Calls per second |
| db.sql\$1tokenized.stats.rows\$1per\$1sec | Rows per second |
| db.sql\$1tokenized.stats.total\$1time\$1per\$1sec | Average active executions per second (AAE) |
| db.sql\$1tokenized.stats.shared\$1blks\$1hit\$1per\$1sec | Block hits per second |
| db.sql\$1tokenized.stats.shared\$1blks\$1read\$1per\$1sec | Block reads per second |
| db.sql\$1tokenized.stats.shared\$1blks\$1dirtied\$1per\$1sec | Blocks dirtied per second |
| db.sql\$1tokenized.stats.shared\$1blks\$1written\$1per\$1sec | Block writes per second |
| db.sql\$1tokenized.stats.local\$1blks\$1hit\$1per\$1sec | Local block hits per second |
| db.sql\$1tokenized.stats.local\$1blks\$1read\$1per\$1sec | Local block reads per second |
| db.sql\$1tokenized.stats.local\$1blks\$1dirtied\$1per\$1sec | Local block dirtied per second |
| db.sql\$1tokenized.stats.local\$1blks\$1written\$1per\$1sec | Local block writes per second |
| db.sql\$1tokenized.stats.temp\$1blks\$1written\$1per\$1sec | Temporary writes per second |
| db.sql\$1tokenized.stats.temp\$1blks\$1read\$1per\$1sec | Temporary reads per second |
| db.sql\$1tokenized.stats.blk\$1read\$1time\$1per\$1sec | Average concurrent reads per second |
| db.sql\$1tokenized.stats.blk\$1write\$1time\$1per\$1sec | Average concurrent writes per second |
## Per-call digest statistics for RDS PostgreSQL
The following metrics provide per call statistics for a SQL statement.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.rows\$1per\$1call | Rows per call |
| db.sql\$1tokenized.stats.avg\$1latency\$1per\$1call | Average latency per call (in ms) |
| db.sql\$1tokenized.stats.shared\$1blks\$1hit\$1per\$1call | Block hits per call |
| db.sql\$1tokenized.stats.shared\$1blks\$1read\$1per\$1call | Block reads per call |
| db.sql\$1tokenized.stats.shared\$1blks\$1written\$1per\$1call | Block writes per call |
| db.sql\$1tokenized.stats.shared\$1blks\$1dirtied\$1per\$1call | Blocks dirtied per call |
| db.sql\$1tokenized.stats.local\$1blks\$1hit\$1per\$1call | Local block hits per call |
| db.sql\$1tokenized.stats.local\$1blks\$1read\$1per\$1call | Local block reads per call |
| db.sql\$1tokenized.stats.local\$1blks\$1dirtied\$1per\$1call | Local block dirtied per call |
| db.sql\$1tokenized.stats.local\$1blks\$1written\$1per\$1call | Local block writes per call |
| db.sql\$1tokenized.stats.temp\$1blks\$1written\$1per\$1call | Temporary block writes per call |
| db.sql\$1tokenized.stats.temp\$1blks\$1read\$1per\$1call | Temporary block reads per call |
| db.sql\$1tokenized.stats.blk\$1read\$1time\$1per\$1call | Read time per call (in ms) |
| db.sql\$1tokenized.stats.blk\$1write\$1time\$1per\$1call | Write time per call (in ms) |
## Primary statistics for RDS PostgreSQL
The following SQL statistics are available for PostgreSQL DB instances.
| Metric | Unit |
| --- | --- |
| db.sql\$1tokenized.stats.calls | Calls |
| db.sql\$1tokenized.stats.rows | Rows |
| db.sql\$1tokenized.stats.total\$1time | Total time (in ms) |
| db.sql\$1tokenized.stats.shared\$1blks\$1hit | Block hits |
| db.sql\$1tokenized.stats.shared\$1blks\$1read | Block reads |
| db.sql\$1tokenized.stats.shared\$1blks\$1dirtied | Blocks dirtied |
| db.sql\$1tokenized.stats.shared\$1blks\$1written | Block writes |
| db.sql\$1tokenized.stats.local\$1blks\$1hit | Local block hits |
| db.sql\$1tokenized.stats.local\$1blks\$1read | Local block reads |
| db.sql\$1tokenized.stats.local\$1blks\$1dirtied | Local blocks dirtied |
| db.sql\$1tokenized.stats.local\$1blks\$1written | Local block writes |
| db.sql\$1tokenized.stats.temp\$1blks\$1written | Temporary writes |
| db.sql\$1tokenized.stats.temp\$1blks\$1read | Temporary reads |
| db.sql\$1tokenized.stats.blk\$1read\$1time | Average concurrent reads (in ms) |
| db.sql\$1tokenized.stats.blk\$1write\$1time | Average concurrent writes (in ms) |
For more information about these metrics, see [pg\$1stat\$1statements](https://www.postgresql.org/docs/current/pgstatstatements.html) in the PostgreSQL documentation.
# OS metrics in Enhanced Monitoring
Amazon RDS provides metrics in real time for the operating system (OS) that your DB instance runs on. RDS delivers the metrics from Enhanced Monitoring to your Amazon CloudWatch Logs account. The following tables list the OS metrics available using Amazon CloudWatch Logs.
**Topics**
+ [
## OS metrics for Db2, MariaDB, MySQL, Oracle, and PostgreSQL
](#USER_Monitoring-Available-OS-Metrics-RDS)
+ [
## OS metrics for Microsoft SQL Server
](#USER_Monitoring-Available-OS-Metrics-RDS.SQLServer)
## OS metrics for Db2, MariaDB, MySQL, Oracle, and PostgreSQL
RDS collects disk metrics for `rdsdbdata` as well as additional storage volumes present in the OS. To view OS metrics in CloudWatch Logs, see [Viewing OS metrics using CloudWatch Logs](USER_Monitoring.OS.CloudWatchLogs.md).
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_Monitoring-Available-OS-Metrics.html)
## OS metrics for Microsoft SQL Server
RDS collects disk metrics for `rdsdbdata` as well as additional storage volumes present in the OS. To view OS metrics in CloudWatch Logs, see [Viewing OS metrics using CloudWatch Logs](USER_Monitoring.OS.CloudWatchLogs.md).
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_Monitoring-Available-OS-Metrics.html)