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:
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You use the same compute option that was used on premises.
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You lack awareness of the cloud compute options, features, and solutions, and how those solutions might improve your compute performance.
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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
The following steps guide you through selecting the right compute options to match your workload characteristics and performance requirements.
Implementation steps
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Understand your workload compute requirements. Key requirements to consider include processing needs, traffic patterns, data access patterns, scaling needs, and latency requirements.
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Learn about different compute options available for your workload on AWS (as outlined in 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.
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Perform experiments and benchmarking in a non-production environment to identify which compute option can best address your workload requirements.
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Once you have experimented and identified your new compute solution, plan your migration and validate your performance metrics.
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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
Related documents:
Related videos:
Related examples:
