AWS Well-Architected Framework - Sustainability Pillar

Environmental sustainability is a shared responsibility between customers and AWS.

• AWS is responsible for optimizing the sustainability of the cloud – delivering efficient, shared infrastructure, water stewardship, and sourcing renewable power.
• Customers are responsible for sustainability in the cloud – optimizing workloads and resource utilization, and minimizing the total resources required to be deployed for your workloads.

Maximize utilization: Right-size workloads and implement efficient design to ensure high utilization and maximize the energy efficiency of the underlying hardware. Two hosts running at 30% utilization are less efficient than one host running at 60% due to baseline power consumption per host. At the same time, eliminate or minimize idle resources, processing, and storage to reduce the total energy required to power your workload.

When you evaluate specific changes, you must also evaluate which metrics best quantify the effect of that change on the associated resource. These metrics are called proxy metrics. Select proxy metrics that best reflect the type of improvement you are evaluating and the resources targeted by improvement. These metrics might evolve over time.

Meeting sustainability targets might not require equivalent trade-offs in one or more other traditional metrics such as uptime, availability, or response time. You can achieve significant gains in sustainability with no measurable impact on service levels. Where minor trade-offs are required, the sustainability improvements gained by these trade-offs can outweigh the change in quality of service.

SUS03-BP01 Optimize software and architecture for asynchronous and scheduled jobs

Use efficient software and architecture patterns such as queue-driven to maintain consistent high utilization of deployed resources.

Common anti-patterns:

• You overprovision the resources in your cloud workload to meet unforeseen spikes in demand.
• Your architecture does not decouple senders and receivers of asynchronous messages by a messaging component.

Benefits of establishing this best practice:

• efficient software and architecture patterns minimize the unused resources in your workload and improve the overall efficiency.
• You can scale the processing independently of the receiving of asynchronous messages.
• Through a messaging component, you have relaxed availability requirements that you can meet with fewer resources.

SUS03-BP02 Remove or refactor workload components with low or no use

Remove components that are unused and no longer required, and refactor components with little utilization to minimize waste in your workload.

Common anti-patterns:

• You do not regularly check the utilization level of individual components of your workload.
• You do not check and analyze recommendations from AWS rightsizing tools such as AWS Compute Optimizer.

Benefits of establishing this best practice:
Removing unused components minimizes waste and improves the overall efficiency of your cloud workload.

SUS03-BP05 Use software patterns and architectures that best support data access and storage patterns

Understand how data is used within your workload, consumed by your users, transferred, and stored. Use software patterns and architectures that best support data access and storage to minimize the compute, networking, and storage resources required to support the workload.

Common anti-patterns:

• You assume that all workloads have similar data storage and access patterns.
• You only use one tier of storage, assuming all workloads fit within that tier.#
• You assume that data access patterns will stay consistent over time.
• Your architecture supports a potential high data access burst, which results in the resources remaining idle most of the time.

Benefits of establishing this best practice:
Selecting and optimizing your architecture based on data access and storage patterns will help decrease development complexity and increase overall utilization. Understanding when to use global tables, data partitioning, and caching will help you decrease operational overhead and scale based on your workload needs.

SUS04-BP07 Minimize data movement across networks

Use shared file systems or object storage to access common data and minimize the total networking resources required to support data movement for your workload.

Common anti-patterns:

• You store all data in the same AWS Region independent of where the data users are.
• You do not optimize data size and format before moving it over the network.

Benefits of establishing this best practice:
Optimizing data movement across the network reduces the total networking resources required for the workload and lowers its environmental impact.

SUS05-BP01 Use the minimum amount of hardware to meet your needs

Use the minimum amount of hardware for your workload to efficiently meet your business needs.

Common anti-patterns:

• You do not monitor resource utilization.
• You have resources with a low utilization level in your architecture.
• You do not review the utilization of static hardware to determine if it should be resized.
• You do not set hardware utilization goals for your compute infrastructure based on business KPIs.

Benefits of establishing this best practice:
Rightsizing your cloud resources helps to reduce a workload’s environmental impact, save money, and maintain performance benchmarks.

Make trade-offs that significantly reduce sustainability impacts in exchange for acceptable decreases in service levels.

• Sustainability and reliability: Highly available workloads tend to consume more resources.
• Sustainability and performance: Using more resources to boost performance could have a higher environmental impact.
• Sustainability and security: Overly secure workloads could have a higher environmental impact.

Use managed services: Sharing services across a broad customer base helps maximize resource utilization, which reduces the amount of infrastructure needed to support cloud workloads. For example, customers can share the impact of common data center components like power and networking by migrating workloads to the AWS Cloud and adopting managed services, such as AWS Fargate for serverless containers, where AWS operates at scale and is responsible for their efficient operation. Use managed services that can help minimize your impact, such as automatically moving infrequently accessed data to cold storage with Amazon S3 Lifecycle configurations or Amazon EC2 Auto Scaling to adjust capacity to meet demand.