PERF02-BP02 Understand the available compute configuration and features
Understand the available configuration options and features for your compute service to help you provision the right amount of resources and improve performance efficiency.
Common anti-patterns:
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You do not evaluate compute options or available instance families against workload characteristics.
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You over-provision compute resources to meet peak-demand requirements.
Benefits of establishing this best practice: Be familiar with AWS compute features and configurations so that you can use a compute solution optimized to meet your workload characteristics and needs.
Level of risk exposed if this best practice is not established: Medium
Implementation guidance
Each compute solution has unique configurations and features
available to support different workload characteristics and
requirements. Learn how these options complement your workload,
and determine which configuration options are best for your
application. Examples of these options include instance family,
sizes, features (GPU, I/O), bursting, time-outs, function sizes,
container instances, and concurrency. If your workload has been
using the same compute option for more than four weeks and you
anticipate that the characteristics will remain the same in the
future, you can
use AWS Compute Optimizer
Implementation steps
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Understand workload requirements (like CPU need, memory, and latency).
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Review AWS documentation and best practices to learn about recommended configuration options that can help improve compute performance. Here are some key configuration options to consider:
Configuration option Examples Instance type -
Compute-optimized
instances are ideal for the workloads that require high higher vCPU to memory ratio. -
Memory-optimized
instances deliver large amounts of memory to support memory intensive workloads. -
Storage-optimized
instances are designed for workloads that require high, sequential read and write access (IOPS) to local storage.
Pricing model -
On-Demand Instances
let you use the compute capacity by the hour or second with no long-term commitment. These instances are good for bursting above performance baseline needs. -
Savings Plans
offer significant savings over On-Demand Instances in exchange for a commitment to use a specific amount of compute power for a one or three-year period. -
Spot Instances
let you take advantage of unused instance capacity at a discount for your stateless, fault-tolerant workloads.
Auto Scaling Use Auto Scaling configuration to match compute resources to traffic patterns. Sizing -
Use Compute Optimizer
to get a machine-learning powered recommendations on which compute configuration best matches your compute characteristics. -
Use AWS Lambda Power Tuning to select the best configuration for your Lambda function.
Hardware-based compute accelerators -
Accelerated computing instances perform functions like graphics processing or data pattern matching more efficiently than CPU-based alternatives.
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For machine learning workloads, take advantage of purpose-built hardware that is specific to your workload, such as AWS Trainium
, AWS Inferentia , and Amazon EC2 DL1
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Resources
Related documents:
Related videos:
Related examples:
