PERF02-BP01 Select the best compute options for your workload - Performance Efficiency Pillar
Implementation guidanceImplementation stepsResources

PERF02-BP01 Select the best compute options for your workload

Selecting the most appropriate compute option for your workload allows you to improve performance, reduce unnecessary infrastructure costs, and lower the operational efforts required to maintain your workload.

Common anti-patterns:

  • You use the same compute option that was used on premises.

  • You lack awareness of the cloud compute options, features, and solutions, and how those solutions might improve your compute performance.

  • You over-provision an existing compute option to meet scaling or performance requirements when an alternative compute option would align to your workload characteristics more precisely.

Benefits of establishing this best practice: By identifying the compute requirements and evaluating against the options available, you can make your workload more resource efficient.

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

Implementation guidance

To optimize your cloud workloads for performance efficiency, it is important to select the most appropriate compute options for your use case and performance requirements. AWS provides a variety of compute options that cater to different workloads in the cloud. For instance, you can use Amazon EC2 to launch and manage virtual servers, AWS Lambda to run code without having to provision or manage servers, Amazon ECS or Amazon EKS to run and manage containers, or AWS Batch to process large volumes of data in parallel. Based on your scale and compute needs, you should choose and configure the optimal compute solution for your situation. You can also consider using multiple types of compute solutions in a single workload, as each one has its own advantages and drawbacks.

The following steps guide you through selecting the right compute options to match your workload characteristics and performance requirements.

Implementation steps

  • Understand your workload compute requirements. Key requirements to consider include processing needs, traffic patterns, data access patterns, scaling needs, and latency requirements.

  • Learn about different AWS compute services for your workload. For more information, see PERF01-BP01 Learn about and understand available cloud services and features. Here are some key AWS compute options, their characteristics, and common use cases:

    AWS service Key characteristics Common use cases
    Amazon Elastic Compute Cloud (Amazon EC2) Has dedicated option for hardware, license requirements, large selection of different instance families, processor types and compute accelerators Lift and shift migrations, monolithic application, hybrid environments, enterprise applications
    Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS)  Easy deployment, consistent environments, scalable Microservices, hybrid environments
    AWS Lambda  Serverless compute service that runs code in response to events and automatically manages the underlying compute resources. Microservices, event-driven applications
    AWS Batch Efficiently and dynamically provisions and scales Amazon Elastic Container Service (Amazon ECS), Amazon Elastic Kubernetes Service (Amazon EKS), and AWS Fargate compute resources, with an option to use On-Demand or Spot Instances based on your job requirements HPC, train ML models
    Amazon Lightsail Preconfigured Linux and Windows application for running small workloads Simple web applications, custom website

  • Evaluate cost (like hourly charge or data transfer) and management overhead (like patching and scaling) associated to each compute option.

  • Perform experiments and benchmarking in a non-production environment to identify which compute option can best address your workload requirements.

  • Once you have experimented and identified your new compute solution, plan your migration and validate your performance metrics.

  • Use AWS monitoring tools like Amazon CloudWatch and optimization services like AWS Compute Optimizer to continually optimize your compute resources based on real-world usage patterns.

Resources

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