Hardware patterns - AWS Well-Architected Framework

Hardware patterns

Look for opportunities to reduce workload sustainability impacts by making changes to your hardware management practices. Minimize the amount of hardware needed to provision and deploy, and select the most efficient hardware for your individual workload.

The following question focuses on these considerations for sustainability:

SUS 5:  How do your hardware management and usage practices support your sustainability goals?

Look for opportunities to reduce workload sustainability impacts by making changes to your hardware management practices. Minimize the amount of hardware needed to provision and deploy, and select the most efficient hardware for your individual workload.

Use the minimum amount of hardware to meet your needs: Using the capabilities of the cloud, you can make frequent changes to your workload implementations. Update deployed components as your needs change.

Use instance types with the least impact: Continually monitor the release of new instance types and take advantage of energy efficiency improvements, including those instance types designed to support specific workloads such as machine learning training and inference, and video transcoding.

Use managed services: Managed services shift responsibility for maintaining high average utilization, and sustainability optimization of the deployed hardware, to AWS. Use managed services to distribute the sustainability impact of the service across all tenants of the service, reducing your individual contribution.

Optimize your use of GPUs: Graphics processing units (GPUs) can be a source of high-power consumption, and many GPU workloads are highly variable, such as rendering, transcoding, and machine learning training and modeling. Only run GPUs instances for the time needed, and decommission them with automation when not required to minimize resources consumed.