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 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 24 hours to be generated, and sufficient metric data must be accumulated. For more information, see Resource 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.

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.

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, Redis, Kafka, or SQLServer. 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.

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.

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

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

Estimated monthly savings and savings opportunity

Estimated monthly savings (after discounts)

This column lists the approximate monthly cost savings that you experience by migrating your workloads from the current instance type to the recommended instance type under the Savings Plans and Reserved Instances pricing models. To receive recommendations with Savings Plans and Reserved Instances discounts, the savings estimation mode preference needs to be activated. For more information, see Savings estimation mode.

Estimated monthly savings (On-Demand)

This column lists the approximate monthly cost savings that you experience by migrating your workloads from the current instance type to the recommended instance type under the On-Demand pricing model.

Savings opportunity (%)

This column lists the percentage difference between the price of the current instance and the price of the recommended instance type. If savings estimation mode is activated, Compute Optimizer analyzes the Savings Plans and Reserved Instances pricing discounts to generate the savings opportunity percentage. If savings estimation mode isn’t activated, Compute Optimizer only uses On-Demand pricing information. For more information, see Savings estimation mode.

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.

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 analysis period. Compute Optimizer uses the maximum utilization point within each five-minute time interval to generate Auto Scaling group recommendations.

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: