PERF02-BP04 Configure and right-size compute resources

Configure and right-size compute resources to match your workload’s performance requirements and avoid under- or over-utilized resources.

Common anti-patterns:

• You ignore your workload performance requirements resulting in over-provisioned or under-provisioned compute resources.

• You only choose the largest or smallest instance available for all workloads.

• You only use one instance family for ease of management.

• You ignore recommendations from AWS Cost Explorer or Compute Optimizer for right-sizing.

• You do not re-evaluate the workload for suitability of new instance types.

• You certify only a small number of instance configurations for your organization.

Benefits of establishing this best practice: Right-sizing compute resources ensures optimal operation in the cloud by avoiding over-provisioning and under-provisioning resources. Properly sizing compute resources typically results in better performance and enhanced customer experience, while also lowering cost.

Level of risk exposed if this best practice is not established: Medium

Implementation guidance

Right-sizing allows organizations to operate their cloud infrastructure in an efficient and cost-effective manner while addressing their business needs. Over-provisioning cloud resources can lead to extra costs, while under-provisioning can result in poor performance and a negative customer experience. AWS provides tools such as AWS Compute Optimizer and AWS Trusted Advisor that use historical data to provide recommendations to right-size your compute resources.

Implementation steps

• Choose an instance type to best fit your needs:

  • How do I choose the appropriate Amazon EC2 instance type for my workload?

  • Attribute-based instance type selection for Amazon EC2 Fleet

  • Create an Auto Scaling group using attribute-based instance type selection

  • Optimizing your Kubernetes compute costs with Karpenter consolidation

• Analyze the various performance characteristics of your workload and how these characteristics relate to memory, network, and CPU usage. Use this data to choose resources that best match your workload's profile and performance goals.

• Monitor your resource usage using AWS monitoring tools such as Amazon CloudWatch.

• Select the right configuration for compute resources.

  • For ephemeral workloads, evaluate instance Amazon CloudWatch metrics such as CPUUtilization to identify if the instance is under-utilized or over-utilized.

  • For stable workloads, check AWS rightsizing tools such as AWS Compute Optimizer and AWS Trusted Advisor at regular intervals to identify opportunities to optimize and right-size the compute resource.

    • Well-Architected Lab - Rightsizing Recommendations 

    • Well-Architected Lab - Rightsizing with Compute Optimizer 

• Test configuration changes in a non-production environment before implementing in a live environment.

• Continually re-evaluate new compute offerings and compare against your workload’s needs.

Resources

Related documents:

• Cloud Compute with AWS

• Amazon EC2 Instance Types

• Amazon ECS Containers: Amazon ECS Container Instances

• Amazon EKS Containers: Amazon EKS Worker Nodes

• Functions: Lambda Function Configuration

• Processor State Control for Your Amazon EC2 Instance

Related videos:

• Amazon EC2 foundations

• Better, faster, cheaper compute: Cost-optimizing Amazon EC2

• Deploy ML models for inference at high performance and low cost

• Optimize performance and cost for your AWS compute

• Powering next-gen Amazon EC2: Deep dive into the Nitro system

• Simplifying Data Processing to Enhance Innovation with Serverless Tools

Related examples:

• Rightsizing with Compute Optimizer and Memory utilization enabled

• AWS Compute Optimizer Demo code