Accessing RDS DB instance recommendations and details - AWS Compute Optimizer
Procedures

Accessing RDS DB instance recommendations and details

You can use one of the following procedures to access either the RDS DB instance recommendations or the RDS DB instance details pages in the AWS Console.

On the RDS DB instance recommendations page you can view the recommendations for your RDS DB instances. On the RDS DB instance instance details page you can view the details of a specific instance or storage and its recommendations.

Procedures

To access the RDS DB instance recommendations page

  1. Open the Compute Optimizer console at https://console.aws.amazon.com/compute-optimizer/.

  2. Choose RDS DB instances in the navigation pane.

    Note

    The current instances listed are from the AWS Region that is currently selected, in the selected account.

  3. You can perform the following actions on the recommendations page:

    • View your instance or storage recommendations by choosing the Instance or Storage tab.

    • In the Instance tab only, you can view the price and performance impact of running your workload on AWS Graviton-based instances. To do this, choose Graviton (aws-arm64) in the CPU architecture preference dropdown list. Otherwise, the Current (default) option displays recommendations that are based on the same CPU vendor and architecture as the current RDS DB instance.

    • Filter instance or storage recommendations to one or mores AWS Regions. To do this, enter the name of the Region in the Filter by one or more properties text box, or choose one or more Regions in the drop-down list that appears.

    • Filter your instance or storage recommendations by tags. To do this, first select the Tag key or Tag value text box. Then, enter the key or value that you want to filter your RDS instance recommendations by.

      For example, to find all the recommendations that have a tag with the key of Owner and the value of TeamA, specify tag:Owner for the filter name and TeamA for the filter value.

    • View instance or storage recommendations in another account. To do this, choose Account, and then select a different account ID.

      Note

      If you're signed in to a management account of an organization and trusted access with Compute Optimizer is enabled, you can view recommendations for resources in other accounts. For more information, see Accounts supported by Compute Optimizer and Trusted access for AWS Organizations.

    • Clear the selected filters. To do this, choose Clear filters next to the filter.

To access the RDS DB instance details page

  1. Open the Compute Optimizer console at https://console.aws.amazon.com/compute-optimizer/.

  2. Choose RDS DB instances in the navigation pane.

  3. Choose the finding classification listed next to the RDS DB instance or storage volume that you want to view.

  4. You can perform the following actions on the details page:

    • View your instance or storage recommendations by choosing the Instance or Storage tab.

    • In the Instance tab only, you can view the price and performance impact of running your workload on AWS Graviton-based instances, choose Graviton (aws-arm64) in the CPU architecture preference dropdown. Otherwise, the Current (default) option displays recommendations that are based on the same CPU vendor and architecture as the current RDS DB instance.

    • On the comparison graphs, you can hover over the graph to see exact values on specific dates over the analysis period.

    • To change the time range of the graphs, choose Time Range, and then choose Last 24 hours, Last 3 days, Last week, or Last 2 weeks.

      Choosing a shorter time range displays the data points at a higher granularity, which provides a higher level of detail.

    • To change the statistic value of the graphs, choose Statistics, and then choose Average or Maximum.

      You can use this option to determine the typical Amazon RDS utilization of your workload over time. To view the highest value observed during the specified period, change the selection to Maximum. This way, you can determine the peak instance usage of your workload over time.