# SUS 3 How do you take advantage of software and architecture patterns to support your sustainability goals?
Implement patterns for performing load smoothing and maintaining consistent high utilization of deployed resources to minimize the resources consumed. Components might become idle from lack of use because of changes in user behavior over time. Revise patterns and architecture to consolidate under-utilized components to increase overall utilization. Retire components that are no longer required. Understand the performance of your workload components, and optimize the components that consume the most resources. Be aware of the devices that your customers use to access your services, and implement patterns to minimize the need for device upgrades.
**Topics**
+ [SUS03-BP01 Optimize software and architecture for asynchronous and scheduled jobs](sus_sus_software_a2.md)
+ [SUS03-BP02 Remove or refactor workload components with low or no use](sus_sus_software_a3.md)
+ [SUS03-BP03 Optimize areas of code that consume the most time or resources](sus_sus_software_a4.md)
+ [SUS03-BP04 Optimize impact on devices and equipment](sus_sus_software_a5.md)
+ [SUS03-BP05 Use software patterns and architectures that best support data access and storage patterns](sus_sus_software_a6.md)
# 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.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Use efficient architecture patterns such as [event-driven architecture](https://aws.amazon.com/event-driven-architecture/) that result in even utilization of components and minimize overprovisioning in your workload. Using efficient architecture patterns minimizes idle resources from lack of use due to changes in demand over time.
Understand the requirements of your workload components and adopt architecture patterns that increase overall utilization of resources. Retire components that are no longer required.
**Implementation steps**
+ Analyze the demand for your workload to determine how to respond to those.
+ For requests or jobs that don’t require synchronous responses, use queue-driven architectures and auto scaling workers to maximize utilization. Here are some examples of when you might consider queue-driven architecture:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2023-04-10/framework/sus_sus_software_a2.html)
+ For requests or jobs that can be processed anytime, use scheduling mechanisms to process jobs in batch for more efficiency. Here are some examples of scheduling mechanisms on AWS:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2023-04-10/framework/sus_sus_software_a2.html)
+ If you use polling and webhooks mechanisms in your architecture, replace those with events. Use [event-driven architectures](https://docs.aws.amazon.com/lambda/latest/operatorguide/event-driven-architectures.html) to build highly efficient workloads.
+ Leverage [serverless on AWS](https://aws.amazon.com/serverless/) to eliminate over-provisioned infrastructure.
+ Right size individual components of your architecture to prevent idling resources waiting for input.
## Resources
**Related documents:**
+ [What is Amazon Simple Queue Service?](https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/welcome.html)
+ [What is Amazon MQ?](https://docs.aws.amazon.com/amazon-mq/latest/developer-guide/welcome.html)
+ [Scaling based on Amazon SQS](https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-using-sqs-queue.html)
+ [What is AWS Step Functions?](https://docs.aws.amazon.com/step-functions/latest/dg/welcome.html)
+ [What is AWS Lambda?](https://docs.aws.amazon.com/lambda/latest/dg/welcome.html)
+ [Using AWS Lambda with Amazon SQS](https://docs.aws.amazon.com/lambda/latest/dg/with-sqs.html)
+ [What is Amazon EventBridge?](https://docs.aws.amazon.com/eventbridge/latest/userguide/what-is-amazon-eventbridge.html)
**Related videos:**
+ [Moving to event-driven architectures](https://www.youtube.com/watch?v=h46IquqjF3E)
# 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](https://aws.amazon.com/compute-optimizer/).
**Benefits of establishing this best practice:** Removing unused components minimizes waste and improves the overall efficiency of your cloud workload.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Review your workload to identify idle or unused components. This is an iterative improvement process which can be initiated by changes in demand or the release of a new cloud service. For example, a significant drop in [AWS Lambda](https://docs.aws.amazon.com/lambda/) function run time can be an indicator of a need to lower the memory size. Also, as AWS releases new services and features, the optimal services and architecture for your workload may change.
Continually monitor workload activity and look for opportunities to improve the utilization level of individual components. By removing idle components and performing rightsizing activities, you meet your business requirements with the fewest cloud resources.
**Implementation steps**
+ Monitor and capture the utilization metrics for critical components of your workload (like CPU utilization, memory utilization, or network throughput in [Amazon CloudWatch metrics](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/working_with_metrics.html)).
+ For stable workloads, check AWS rightsizing tools such as [AWS Compute Optimizer](https://aws.amazon.com/compute-optimizer/) at regular intervals to identify idle, unused, or underutilized components.
+ For ephemeral workloads, evaluate utilization metrics to identify idle, unused, or underutilized components.
+ Retire components and associated assets (like Amazon ECR images) that are no longer needed.
+ Refactor or consolidate underutilized components with other resources to improve utilization efficiency. For example, you can provision multiple small databases on a single [Amazon RDS](https://aws.amazon.com/rds/) database instance instead of running databases on individual under-utilized instances.
+ Understand the [resources provisioned by your workload to complete a unit of work](https://docs.aws.amazon.com/wellarchitected/latest/sustainability-pillar/evaluate-specific-improvements.html).
## Resources
**Related documents:**
+ [AWS Trusted Advisor](https://aws.amazon.com/premiumsupport/technology/trusted-advisor/)
+ [What is Amazon CloudWatch?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/WhatIsCloudWatch.html)
+ [Automated Cleanup of Unused Images in Amazon ECR](https://aws.amazon.com/blogs/compute/automated-cleanup-of-unused-images-in-amazon-ecr/)
**Related examples:**
+ [ Well-Architected Lab - Rightsizing with AWS Compute Optimizer](https://wellarchitectedlabs.com/cost/200_labs/200_aws_resource_optimization/)
+ [ Well-Architected Lab - Optimize Hardware Patterns and Observe Sustainability KPIs ](https://wellarchitectedlabs.com/sustainability/200_labs/200_optimize_hardware_patterns_observe_sustainability_kpis/)
# SUS03-BP03 Optimize areas of code that consume the most time or resources
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| This best practice was updated with new guidance on July 13th, 2023. |
Optimize your code that runs within different components of your architecture to minimize resource usage while maximizing performance.
**Common anti-patterns:**
+ You ignore optimizing your code for resource usage.
+ You usually respond to performance issues by increasing the resources.
+ Your code review and development process does not track performance changes.
**Benefits of establishing this best practice:** Using efficient code minimizes resource usage and improves performance.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
It is crucial to examine every functional area, including the code for a cloud architected application, to optimize its resource usage and performance. Continually monitor your workload’s performance in build environments and production and identify opportunities to improve code snippets that have particularly high resource usage. Adopt a regular review process to identify bugs or anti-patterns within your code that use resources inefficiently. Leverage simple and efficient algorithms that produce the same results for your use case.
## Implementation steps
+ While developing your workloads, adopt an automated code review process to improve quality and identify bugs and anti-patterns.
+ [ Automate code reviews with Amazon CodeGuru Reviewer ](https://aws.amazon.com/blogs/devops/automate-code-reviews-with-amazon-codeguru-reviewer/)
+ [ Detecting concurrency bugs with Amazon CodeGuru ](https://aws.amazon.com/blogs/devops/detecting-concurrency-bugs-with-amazon-codeguru/)
+ [ Raising code quality for Python applications using Amazon CodeGuru ](https://aws.amazon.com/blogs/devops/raising-code-quality-for-python-applications-using-amazon-codeguru/)
+ As you run your workloads, monitor resources to identify components with high resource requirements per unit of work as targets for code reviews.
+ For code reviews, use a code profiler to identify the areas of code that use the most time or resources as targets for optimization.
+ [ Reducing your organization's carbon footprint with Amazon CodeGuru Profiler ](https://aws.amazon.com/blogs/devops/reducing-your-organizations-carbon-footprint-with-codeguru-profiler/)
+ [ Understanding memory usage in your Java application with Amazon CodeGuru Profiler ](https://aws.amazon.com/blogs/devops/understanding-memory-usage-in-your-java-application-with-amazon-codeguru-profiler/)
+ [ Improving customer experience and reducing cost with Amazon CodeGuru Profiler ](https://aws.amazon.com/blogs/devops/improving-customer-experience-and-reducing-cost-with-codeguru-profiler/)
+ Use the most efficient operating system and programming language for the workload. For details on energy efficient programming languages (including Rust), see [Sustainability with Rust](https://aws.amazon.com/blogs/opensource/sustainability-with-rust/).
+ Replace computationally intensive algorithms with simpler and more efficient version that produce the same result.
+ Remove unnecessary code such as sorting and formatting.
## Resources
**Related documents:**
+ [What is Amazon CodeGuru Profiler?](https://docs.aws.amazon.com/codeguru/latest/profiler-ug/what-is-codeguru-profiler.html)
+ [FPGA instances](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/fpga-getting-started.html)
+ [The AWS SDKs on Tools to Build on AWS](https://aws.amazon.com/tools/)
**Related videos:**
+ [ Improve Code Efficiency Using Amazon CodeGuru Profiler ](https://www.youtube.com/watch?v=1pU4VddsBRw)
+ [ Automate Code Reviews and Application Performance Recommendations with Amazon CodeGuru ](https://www.youtube.com/watch?v=OD8H63C0E0I)
# SUS03-BP04 Optimize impact on devices and equipment
Understand the devices and equipment used in your architecture and use strategies to reduce their usage. This can minimize the overall environmental impact of your cloud workload.
**Common anti-patterns:**
+ You ignore the environmental impact of devices used by your customers.
+ You manually manage and update resources used by customers.
**Benefits of establishing this best practice:** Implementing software patterns and features that are optimized for customer device can reduce the overall environmental impact of cloud workload.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Implementing software patterns and features that are optimized for customer devices can reduce the environmental impact in several ways:
+ Implementing new features that are backward compatible can reduce the number of hardware replacements.
+ Optimizing an application to run efficiently on devices can help to reduce their energy consumption and extend their battery life (if they are powered by battery).
+ Optimizing an application for devices can also reduce the data transfer over the network.
Understand the devices and equipment used in your architecture, their expected lifecycle, and the impact of replacing those components. Implement software patterns and features that can help to minimize the device energy consumption, the need for customers to replace the device and also upgrade it manually.
**Implementation steps**
+ Inventory the devices used in your architecture. Devices can be mobile, tablet, IOT devices, smart light, or even smart devices in a factory.
+ Optimize the application running on the devices:
+ Use strategies such as running tasks in the background to reduce their energy consumption.
+ Account for network bandwidth and latency when building payloads, and implement capabilities that help your applications work well on low bandwidth, high latency links.
+ Convert payloads and files into optimized formats required by devices. For example, you can use [Amazon Elastic Transcoder](https://docs.aws.amazon.com/elastic-transcoder/) or [AWS Elemental MediaConvert](https://aws.amazon.com/mediaconvert/) to convert large, high quality digital media files into formats that users can play back on mobile devices, tablets, web browsers, and connected televisions.
+ Perform computationally intense activities server-side (such as image rendering), or use application streaming to improve the user experience on older devices.
+ Segment and paginate output, especially for interactive sessions, to manage payloads and limit local storage requirements.
+ Use automated over-the-air (OTA) mechanism to deploy updates to one or more devices.
+ You can use a [CI/CD pipeline](https://aws.amazon.com/blogs/mobile/build-a-cicd-pipeline-for-your-android-app-with-aws-services/) to update mobile applications.
+ You can use [AWS IoT Device Management](https://aws.amazon.com/iot-device-management/) to remotely manage connected devices at scale.
+ To test new features and updates, use managed device farms with representative sets of hardware and iterate development to maximize the devices supported. For more details, see [SUS06-BP04 Use managed device farms for testing](sus_sus_dev_a5.md).
## Resources
**Related documents:**
+ [What is AWS Device Farm?](https://docs.aws.amazon.com/devicefarm/latest/developerguide/welcome.html)
+ [Amazon AppStream 2.0 Documentation](https://docs.aws.amazon.com/appstream2/)
+ [NICE DCV](https://docs.aws.amazon.com/dcv/)
+ [ OTA tutorial for updating firmware on devices running FreeRTOS ](https://docs.aws.amazon.com/freertos/latest/userguide/dev-guide-ota-workflow.html)
**Related videos:**
+ [ Introduction to AWS Device Farm](https://www.youtube.com/watch?v=UiJo_PEZkD4)
# 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.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
Use software and architecture patterns that aligns best to your data characteristics and access patterns. For example, use [modern data architecture on AWS](https://aws.amazon.com/big-data/datalakes-and-analytics/modern-data-architecture/) that allows you to use purpose-built services optimized for your unique analytics use cases. These architecture patterns allow for efficient data processing and reduce the resource usage.
**Implementation steps**
+ Analyze your data characteristics and access patterns to identify the correct configuration for your cloud resources. Key characteristics to consider include:
+ **Data type:** structured, semi-structured, unstructured
+ **Data growth:** bounded, unbounded
+ **Data durability:** persistent, ephemeral, transient
+ **Access patterns** reads or writes, update frequency, spiky, or consistent
+ Use architecture patterns that best support data access and storage patterns.
+ [ Let’s Architect\$1 Modern data architectures ](https://aws.amazon.com/blogs/architecture/lets-architect-modern-data-architectures/)
+ [ Databases on AWS: The Right Tool for the Right Job ](https://www.youtube.com/watch?v=-pb-DkD6cWg)
+ Use technologies that work natively with compressed data.
+ Use purpose-built [analytics services](https://aws.amazon.com/big-data/datalakes-and-analytics/?nc2=h_ql_prod_an_a) for data processing in your architecture.
+ Use the database engine that best supports your dominant query pattern. Manage your database indexes to ensure efficient querying. For further details, see [AWS Databases](https://aws.amazon.com/products/databases/).
+ Select network protocols that reduce the amount of network capacity consumed in your architecture.
## Resources
**Related documents:**
+ [Athena Compression Support file formats](https://docs.aws.amazon.com/athena/latest/ug/compression-formats.html)
+ [COPY from columnar data formats with Amazon Redshift](https://docs.aws.amazon.com/redshift/latest/dg/copy-usage_notes-copy-from-columnar.html)
+ [Converting Your Input Record Format in Firehose](https://docs.aws.amazon.com/firehose/latest/dev/record-format-conversion.html)
+ [Format Options for ETL Inputs and Outputs in AWS Glue](https://docs.aws.amazon.com/glue/latest/dg/aws-glue-programming-etl-format.html)
+ [Improve query performance on Amazon Athena by Converting to Columnar Formats](https://docs.aws.amazon.com/athena/latest/ug/convert-to-columnar.html)
+ [Loading compressed data files from Amazon S3 with Amazon Redshift](https://docs.aws.amazon.com/redshift/latest/dg/t_loading-gzip-compressed-data-files-from-S3.html)
+ [Monitoring DB load with Performance Insights on Amazon Aurora](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/USER_PerfInsights.html)
+ [Monitoring DB load with Performance Insights on Amazon RDS](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.html)
+ [ Amazon S3 Intelligent-Tiering storage class ](https://aws.amazon.com/s3/storage-classes/intelligent-tiering/)
**Related videos:**
+ [ Building modern data architectures on AWS](https://www.youtube.com/watch?v=Uk2CqEt5f0o)