Viewing Auto Scaling group recommendations - AWS Compute Optimizer

Viewing Auto Scaling group recommendations

AWS Compute Optimizer generates instance type recommendations for Amazon EC2 Auto Scaling (Auto Scaling) groups. Recommendations for your Auto Scaling groups are displayed on the following pages of the AWS Compute Optimizer console:

  • The Auto Scaling groups recommendations page lists each of your current Auto Scaling groups, their finding classifications, current instance type, current hourly price for the selected purchasing option, and current configuration. The top recommendation from Compute Optimizer is listed next to each of your Auto Scaling groups, and it includes the recommended instance type, the hourly price for the selected purchasing option, and the price difference between your current instance and the recommendation. Use the recommendations page to compare the current instances of your Auto Scaling groups with their top recommendation, which can help you to decide if you should upsize or downsize your instances.

  • The Auto Scaling group details page, which you can access from the Auto Scaling groups recommendations page, lists up to three optimization recommendations for a specific Auto Scaling group. It lists the specifications for each recommendation, their performance risk, and their hourly prices for the selected purchasing option. The details page also displays utilization metric graphs for the current Auto Scaling group.

The recommendations are refreshed daily. They're generated by analyzing the specifications and utilization metrics of the current Auto Scaling group over a period of the last 14 days, or longer if you activate the enhanced infrastructure metrics paid feature. For more information, see Metrics analyzed by AWS Compute Optimizer.

Keep in mind that Compute Optimizer generates recommendations for Auto Scaling groups that meet a specific set of requirements, recommendations could take up to 12 hours to be generated, and sufficient metric data must be accumulated. For more information, see Supported resources and requirements.

Finding classifications

The Finding column on the Auto Scaling groups recommendations page provides a summary of how each of your Auto Scaling groups performed during the analyzed period.

The following findings classifications apply to Auto Scaling groups.

Classification Description

Not optimized

An Auto Scaling group is considered not optimized when Compute Optimizer has identified a recommendation that can provide better performance or cost for your workload.

Optimized

An Auto Scaling group is considered optimized when Compute Optimizer determines that the group is correctly provisioned to run your workload, based on the chosen instance type. For optimized Auto Scaling groups, Compute Optimizer might sometimes recommend a new generation instance type.

AWS Graviton-based instance recommendations

When viewing Auto Scaling group recommendations, you can view the price and performance impact of running your workload on AWS Graviton-based instances. To do so, choose Graviton (aws-arm64) in the CPU architecture preference dropdown. Otherwise, choose Current to view recommendations that are based on the same CPU vendor and architecture as the current instance.


    Graviton based instance recommendations
Note

The Current price, Recommended price, Price difference, Price difference (%), and Estimated monthly savings columns are updated to provide a price comparison between the current instance type and the instance type of the selected CPU architecture preference. For example, if you choose Graviton (aws-arm64), prices are compared between the current instance type and the recommended Graviton-based instance type.

Inferred workload types

The Inferred workload types column on the Auto Scaling groups recommendations page lists the applications that might be running on instances in the Auto Scaling group as inferred by Compute Optimizer. It does this by analyzing the attributes of instances in the Auto Scaling group, such as the instance name, tags, and configuration. Compute Optimizer can currently infer if your instances are running Amazon EMR, Apache Cassandra, Apache Hadoop, Memcached, NGINX, PostgreSQL, and Redis. By inferring the applications running on your instances, Compute Optimizer is able to identify the effort to migrate your workloads from x86-based instance types to Arm-based AWS Graviton instances types. For more information, see Migration effort in the next section of this guide.

Migration effort

The Migration effort column on the Auto Scaling groups recommendations and Auto Scaling groups details pages lists the level of effort that might be required to migrate from the current instance type to the recommended instance type. For example, the migration effort is Medium if a workload type can't be inferred but an AWS Graviton instance type is recommended. The migration effort is Low if Amazon EMR is the inferred workload type and an AWS Graviton instance type is recommended. The migration effort is Very low if both the current and recommended instance types are of the same CPU architecture. For more information about migrating from x86-based instance types to Arm-based AWS Graviton instances type, see Considerations when transitioning workloads to AWS Graviton2 based Amazon EC2 instances in the AWS Graviton Getting Starged GitHub.

Prices and purchasing options

On the Auto Scaling groups recommendations and Auto Scaling group details pages, you can choose to view the hourly prices for current EC2 instances in your Auto Scaling groups and the recommended instances under different Amazon EC2 purchasing options. For example, you can view the price of your current instance and the recommended instance under the Reserve Instances, standard one-year no upfront purchasing option. Use the pricing information to get an idea of the price difference between your current instance and the recommended instance.


    Purchasing options for EC2 instances in an Auto Scaling group
Important

The prices listed on the recommendations page might not reflect the actual prices you pay for your instances. For more information about finding the actual price of your current instances, see Amazon EC2 Usage Reports in the Amazon Elastic Compute Cloud User Guide.

The following purchasing options can be selected on the recommendations page:

  • On-Demand Instances - An On-Demand Instance is an instance that you use on demand. You have full control over its lifecycle—you decide when to launch, stop, hibernate, start, reboot, and terminate it. No longer-term commitments or upfront payments are needed. For more information about On-Demand Instances, see On-Demand Instances in the Amazon Elastic Compute Cloud User Guide. For more information about pricing, see Amazon EC2 On-Demand Instance Pricing.

  • Reserved Instances (standard one-year or three-year commitment, no upfront) - Reserved Instances provide you with significant savings on your Amazon EC2 costs compared to On-Demand Instance pricing. Reserved Instances are not physical instances, but rather a billing discount applied to the use of On-Demand Instances in your account. For more information about Reserved Instances, see Reserved Instances in the Amazon Elastic Compute Cloud User Guide. For more information about pricing, see Amazon EC2 Reserved Instance Pricing.

For more information about purchasing options, see Instance Purchasing Options in the Amazon Elastic Compute Cloud User Guide.

Estimated monthly savings and savings opportunity

The Estimated monthly savings (On-Demand) and Estimated monthly savings (RI and Savings Plans) columns list the approximate monthly cost savings that you will experience by migrating your Auto Scaling group workloads from the current instance type to the recommended instance type under those pricing models. The Savings opportunity (%) column lists the percentage difference between the On-Demand price of current instances in the Auto Scaling group and the price of the recommended instance type.

Important

Savings opportunity data requires that you opt in to Cost Explorer, as well as activate Receive Amazon EC2 resource recommendations in the Cost Explorer preferences page. That creates a connection between Cost Explorer and Compute Optimizer. With this connection, Cost Explorer generates savings estimates considering the price of existing resources, the price of recommended resources, and historical usage data. Estimated monthly savings reflects the projected dollar savings associated with each of the recommendations generated. For more information, see Enabling Cost Explorer and Optimizing your cost with Rightsizing Recommendations in the Cost Management User Guide.

Estimated monthly savings calculation

For each recommendation, we calculate the cost to operate a new instance using the recommended instance type. Estimated monthly savings are calculated based on the number of running hours for current instances in the Auto Scaling group and the difference in rates between the current instance type and the recommended instance type. The estimated monthly savings for Auto Scaling groups displayed on the Compute Optimizer dashboard is a sum of the estimated monthly savings for all over-provisioned instances in Auto Scaling groups, in the account.

Performance risk

The Performance risk column on the Auto Scaling group details page defines the likelihood of each recommended instance type not meeting the resource needs of your workload. Compute Optimizer calculates an individual performance risk score for each specification of the recommended instance, including CPU, memory, EBS throughput, EBS IOPS, disk throughput, disk IOPS, network throughput, and network PPS. The performance risk of the recommended instance is calculated as the maximum performance risk score across the analyzed resource specifications.

The values range from very low, low, medium, high, and very high. A very low performance risk means that the instance type recommendation is predicted to always provide enough capability. The higher the performance risk is, the more likely you should validate whether the recommendation will meet the performance requirements of your workload before migrating your resource. Decide whether to optimize for performance improvement, for cost reduction, or for a combination of these two. For more information, see Changing the Instance Type in the Amazon Elastic Compute Cloud User Guide.

Note

In the Compute Optimizer API, the AWS Command Line Interface (AWS CLI), and AWS SDKs, performance risk is measured on a scale of 0 (very low) to 4 (very high).


    Performance risk for Auto Scaling group recommendations

Current performance risk

The Current performance risk column on the Auto Scaling groups recommendations page defines the likelihood of each current Auto Scaling group not meeting the resource needs of its workload. The current performance risk values range from very low, low, medium, and high. A very low performance risk means that the current Auto Scaling group is predicted to always provide enough capability. The higher the performance risk is, the more likely you should consider the recommendation generated by Compute Optimizer.

Utilization graphs

The Auto Scaling group details page displays utilization metric graphs for current instances in the group. The graphs display data for the analyzed period (up to 14 days). You can change the graphs to display data for the last 24 hours, three days, one week, or two weeks. If you activate the enhanced infrastructure metrics paid feature, you can view data from the last three months.

The following utilization graphs are displayed on the details page:

Graph name Description

Average CPU utilization (percent)

The average percentage of allocated EC2 compute units used by instances in the Auto Scaling group.

Average Network in (MiB/second)

The number of mebibytes (MiB) per second received on all network interfaces by instances in the Auto Scaling group.

Average Network out (MiB/second)

The number of mebibytes (MiB) per second sent out on all network interfaces by instances in the Auto Scaling group.

Viewing Auto Scaling groups recommendations

Use the following procedure to access the Auto Scaling groups recommendations page, and view recommendations for your current Auto Scaling groups.

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

  2. Choose Auto Scaling groups in the navigation pane.

    The recommendations page lists the specifications and finding classifications of your Auto Scaling groups, along with the specifications of the recommended groups. The current Auto Scaling groups 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:

    • To 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 instance.

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

    • To view recommendations for instances in another account, choose Account, and then select a different account ID.

      Note

      The ability to view recommendations for resources in other accounts is available only if you are signed in to a management account of an organization, and trusted access with Compute Optimizer is enabled. For more information, see Accounts supported by Compute Optimizer and Compute Optimizer and AWS Organizations trusted access.

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

    • To change the purchasing option that is displayed, choose Settings (the gear icon), then choose On-Demand Instances, Reserved Instances, standard 1-year no upfront, or Reserved Instances, standard 3-year no upfront.

    • To access the Auto Scaling group details page for a specific Auto Scaling group, choose the finding classification listed next to the desired group.

Viewing Auto Scaling group details

Use the following procedure to access the Auto Scaling group details page, and view details of a specific group and its recommendations.

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

  2. Choose Auto Scaling groups in the navigation pane.

  3. Choose the finding classification listed next to the Auto Scaling group for which you wish to view detailed information.

    The details page lists up to three optimization recommendations for the Auto Scaling group that you chose. It lists the specifications of current instances in the Auto Scaling group, the specifications and performance risks of the recommended instances, and utilization metric graphs.

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

    • To 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 instance.

    • Activate the enhanced infrastructure metrics paid feature to extend the metrics analysis look-back period for the Auto Scaling group you're viewing up to three months (compared to the 14-day default). For more information, see Enhanced infrastructure metrics.

    • The utilization metric graphs for your current instance are displayed at the bottom of the page. The solid blue line is the utilization of current instances in the Auto Scaling group.

    • 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. If you activate the enhanced infrastructure metrics recommendation preference, you can also choose Last 3 months.

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

    • To change the purchasing option that is displayed, choose Settings (the gear icon), then choose On-Demand Instances, Reserved Instances, standard 1-year no upfront, or Reserved Instances, standard 3-year no upfront.