Get EC2 instance recommendations from Compute Optimizer
AWS Compute Optimizer provides Amazon EC2 recommendations to help you improve performance, save money, or both. You can use these recommendations to decide whether to change to a new instance type.
To make recommendations, Compute Optimizer analyzes your existing instance specifications and utilization metrics. The compiled data is then used to recommend which Amazon EC2 instance types are best able to handle the existing workload. Recommendations are returned along with per-hour instance pricing. For more information, see Amazon EC2 instance metrics in the AWS Compute Optimizer User Guide.
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Requirements
To get recommendations from Compute Optimizer, you must first opt in to Compute Optimizer. For more information, see Getting started with AWS Compute Optimizer in the AWS Compute Optimizer User Guide.
Compute Optimizer generates recommendations for some instance types, but not all instance types. If you're using an unsupported instance type, Compute Optimizer will not generate recommendations. For the list of supported instance types, see Amazon EC2 instance requirements in the AWS Compute Optimizer User Guide.
Finding classifications
Compute Optimizer classifies its findings for EC2 instances as follows:
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Under-provisioned – An EC2 instance is considered under-provisioned when at least one specification of your instance, such as CPU, memory, or network, does not meet the performance requirements of your workload. Under-provisioned EC2 instances might lead to poor application performance.
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Over-provisioned – An EC2 instance is considered over-provisioned when at least one specification of your instance, such as CPU, memory, or network, can be sized down while still meeting the performance requirements of your workload, and when no specification is under-provisioned. Over-provisioned EC2 instances might lead to unnecessary infrastructure cost.
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Optimized – An EC2 instance is considered optimized when all specifications of your instance, such as CPU, memory, and network, meet the performance requirements of your workload, and the instance is not over-provisioned. An optimized EC2 instance runs your workloads with optimal performance and infrastructure cost. For optimized instances, Compute Optimizer might sometimes recommend a new generation instance type.
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None – There are no recommendations for this instance. This might occur if you've been opted in to Compute Optimizer for less than 12 hours, or when the instance has been running for less than 30 hours, or when the instance type is not supported by Compute Optimizer.
View recommendations
After you opt in to Compute Optimizer, you can view the findings that Compute Optimizer generates for your EC2 instances in the Amazon EC2 console. You can then access the Compute Optimizer console to view the recommendations. If you recently opted in, findings might not be reflected in the EC2 console for up to 12 hours.
To view recommendations for an instance using the Amazon EC2 console
Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/
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In the navigation pane, choose Instances.
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Choose the instance ID to open the instance detail page.
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On the instance detail page, in the top summary section, locate AWS Compute Optimizer finding. If there is a finding, we display the finding classification and a link to view the details. Otherwise, we display No recommendations available for this instance.
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If there is a finding, choose View detail. This opens the Recommendations for EC2 instances page in the Compute Optimizer console. The current instance type is labeled Current. There are also up to three instance type recommendations, labeled Option 1, Option 2, and Option 3. This page also shows recent CloudWatch metric data for the instance.
To view recommendations for all instances in all Regions
You can view recommendations for all of your Amazon EC2 instances in all Regions using the Compute Optimizer console. For more information, see Viewing EC2 instances recommendations and Viewing EC2 instance details in the AWS Compute Optimizer User Guide.
Considerations for evaluating recommendations
When you receive a recommendation, you must decide whether to act on it. Before changing an instance type, consider the following:
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The recommendations don’t forecast your usage. Recommendations are based on your historical usage over the most recent 14-day time period. Be sure to choose an instance type that is expected to meet your future resource needs.
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Focus on the graphed metrics to determine whether actual usage is lower than instance capacity. You can also view metric data (average, peak, percentile) in CloudWatch to further evaluate your EC2 instance recommendations. For example, notice how CPU percentage metrics change during the day and whether there are peaks that need to be accommodated. For more information, see Viewing Available Metrics in the Amazon CloudWatch User Guide.
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Compute Optimizer might supply recommendations for burstable performance instances, which are T3, T3a, and T2 instances. If you periodically burst above the baseline, make sure that you can continue to do so based on the vCPUs of the new instance type. For more information, see Key concepts for burstable performance instances.
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If you’ve purchased a Reserved Instance, your On-Demand Instance might be billed as a Reserved Instance. Before you change your current instance type, first evaluate the impact on Reserved Instance utilization and coverage.
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Consider conversions to newer generation instances, where possible.
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When migrating to a different instance family, make sure the current instance type and the new instance type are compatible, for example, in terms of virtualization, architecture, or network type. For more information, see Compatibility for changing the instance type.
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Finally, consider the performance risk rating that's provided for each recommendation. Performance risk indicates the amount of effort you might need to spend in order to validate whether the recommended instance type meets the performance requirements of your workload. We also recommend rigorous load and performance testing before and after making any changes.
