# User behavior patterns
**Topics**
+ [SUS 2 How do you take advantage of user behavior patterns to support your sustainability goals?](sus-02.md)
# SUS 2 How do you take advantage of user behavior patterns to support your sustainability goals?
The way users consume your workloads and other resources can help you identify improvements to meet sustainability goals. Scale infrastructure to continually match user load and ensure that only the minimum resources required to support users are deployed. Align service levels to customer needs. Position resources to limit the network required for users to consume them. Remove existing, unused assets. Identify created assets that are unused and stop generating them. Provide your team members with devices that support their needs with minimized sustainability impact.
**Topics**
+ [SUS02-BP01 Scale infrastructure with user load](sus_sus_user_a2.md)
+ [SUS02-BP02 Align SLAs with sustainability goals](sus_sus_user_a3.md)
+ [SUS02-BP03 Stop the creation and maintenance of unused assets](sus_sus_user_a4.md)
+ [SUS02-BP04 Optimize geographic placement of workloads for user locations](sus_sus_user_a5.md)
+ [SUS02-BP05 Optimize team member resources for activities performed](sus_sus_user_a6.md)
# SUS02-BP01 Scale infrastructure with user load
Identify periods of low or no utilization and scale down resources to eliminate excess capacity and improve efficiency.
**Common anti-patterns:**
+ You do not scale your infrastructure with user load.
+ You manually scale your infrastructure all the time.
+ You leave increased capacity after a scaling event instead of scaling back down.
**Benefits of establishing this best practice:** Configuring and testing workload elasticity will help reduce workload environmental impact, save money, and maintain performance benchmarks. You can take advantage of elasticity in the cloud to automatically scale capacity during and after user load spikes to make sure you are only using the exact number of resources needed to meet the needs of your customers.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
+ Elasticity matches the supply of resources you have against the demand for those resources. Instances, containers, and functions provide mechanisms for elasticity, either in combination with automatic scaling or as a feature of the service. Use elasticity in your architecture to ensure that workload can scale down quickly and easily during the period of low user load:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2022-03-31/framework/sus_sus_user_a2.html)
+ Verify that the metrics for scaling up or down are validated against the type of workload being deployed. If you are deploying a video transcoding application, 100% CPU utilization is expected and should not be your primary metric. You can use a [customized metric](https://aws.amazon.com/blogs/mt/create-amazon-ec2-auto-scaling-policy-memory-utilization-metric-linux/) (such as memory utilization) for your scaling policy if required. To choose the right metrics, consider the following guidance for Amazon EC2:
+ The metric should be a valid utilization metric and describe how busy an instance is.
+ The metric value must increase or decrease proportionally to the number of instances in the Auto Scaling group.
+ Use [dynamic scaling](https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scale-based-on-demand.html) instead of [manual scaling](https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-manual-scaling.html) for your Auto Scaling group. We also recommend that you use [target tracking scaling policies](https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-scaling-target-tracking.html) in your dynamic scaling.
+ Verify that workload deployments can handle both scale-up and scale-down events. Create test scenarios for scale-down events to ensure that the workload behaves as expected. You can use [Activity history](https://docs.aws.amazon.com/autoscaling/ec2/userguide/as-verify-scaling-activity.html) to test and verify a scaling activity for an Auto Scaling group.
+ Evaluate your workload for predictable patterns and proactively scale as you anticipate predicted and planned changes in demand. Use [Predictive Scaling with Amazon EC2 Auto Scaling](https://aws.amazon.com/blogs/compute/introducing-native-support-for-predictive-scaling-with-amazon-ec2-auto-scaling/) to eliminate the need to overprove capacity.
## Resources
**Related documents:**
+ [Getting Started with Amazon EC2 Auto Scaling](https://docs.aws.amazon.com/autoscaling/ec2/userguide/GettingStartedTutorial.html)
+ [Predictive Scaling for EC2, Powered by Machine Learning](https://aws.amazon.com/blogs/aws/new-predictive-scaling-for-ec2-powered-by-machine-learning/)
+ [Analyze user behavior using Amazon OpenSearch Service, Amazon Data Firehose and Kibana](https://aws.amazon.com/blogs/database/analyze-user-behavior-using-amazon-elasticsearch-service-amazon-kinesis-data-firehose-and-kibana/)
+ [What is Amazon CloudWatch?](https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/WhatIsCloudWatch.html)
+ [What is AWS X-Ray?](https://docs.aws.amazon.com/xray/latest/devguide/aws-xray.html)
+ [VPC Flow Logs](https://docs.aws.amazon.com/vpc/latest/userguide/flow-logs.html)
+ [Monitoring DB load with Performance Insights on Amazon RDS](https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/USER_PerfInsights.html)
+ [Introducing Native Support for Predictive Scaling with Amazon EC2 Auto Scaling](https://aws.amazon.com/blogs/compute/introducing-native-support-for-predictive-scaling-with-amazon-ec2-auto-scaling/)
+ [How to create an Amazon EC2 Auto Scaling policy based on a memory utilization metric (Linux)](https://aws.amazon.com/blogs/mt/create-amazon-ec2-auto-scaling-policy-memory-utilization-metric-linux/)
+ [Introducing Karpenter - An Open-Source, High-Performance Kubernetes Cluster Autoscaler](https://aws.amazon.com/blogs/aws/introducing-karpenter-an-open-source-high-performance-kubernetes-cluster-autoscaler/)
**Related videos:**
+ [Better, faster, cheaper compute: Cost-optimizing Amazon EC2 (CMP202-R1)](https://www.youtube.com/watch?v=_dvh4P2FVbw)
**Related examples:**
+ [Lab: Amazon EC2 Auto Scaling Group Examples](https://github.com/aws-samples/amazon-ec2-auto-scaling-group-examples)
+ [Lab: Implement Autoscaling with Karpenter](https://www.eksworkshop.com/beginner/085_scaling_karpenter/)
# SUS02-BP02 Align SLAs with sustainability goals
Define and update Service Level Agreements (SLAs) such as availability or data retention periods to minimize the number of resources required to support your workload while continuing to meet business requirements.
**Level of risk exposed if this best practice is not established:** Low
## Implementation guidance
+ Define SLAs that support your sustainability goals while meeting your business requirements.
+ Redefine SLAs to meet business requirements, not exceed them.
+ Make trade-offs that significantly reduce sustainability impacts in exchange for acceptable decreases in service levels.
+ Use design patterns that prioritize business-critical functions, and allow lower service levels (such as response time or recovery time objectives) for non-critical functions.
## Resources
**Related documents:**
+ [AWS Service Level Agreements (SLAs)](https://aws.amazon.com/legal/service-level-agreements/?aws-sla-cards.sort-by=item.additionalFields.serviceNameLower&aws-sla-cards.sort-order=asc&awsf.tech-category-filter=*all)
+ [Importance of Service Level Agreement for SaaS Providers](https://aws.amazon.com/blogs/apn/importance-of-service-level-agreement-for-saas-providers/)
**Related videos:**
+ [Building Sustainably on AWS](https://www.youtube.com/watch?v=ARAitMSIxc8)
# SUS02-BP03 Stop the creation and maintenance of unused assets
Analyze application assets (such as pre-compiled reports, datasets, and static images) and asset access patterns to identify redundancy, underutilization, and potential decommission targets. Consolidate generated assets with redundant content (for example, monthly reports with overlapping or common datasets and outputs) to remove the resources consumed when duplicating outputs. Decommission unused assets (for example, images of products that are no longer sold) to free consumed resources and reduce the number of resources used to support the workload.
**Level of risk exposed if this best practice is not established:** Low
## Implementation guidance
+ Manage static assets and remove assets that are no longer required.
+ Manage generated assets and stop generating and remove assets that are no longer required.
+ Consolidate overlapping generated assets to remove redundant processing.
+ Instruct third parties to stop producing and storing assets managed on your behalf that are no longer required.
+ Instruct third parties to consolidate redundant assets produced on your behalf.
## Resources
**Related documents:**
+ [Optimizing your AWS Infrastructure for Sustainability, Part II: Storage](https://aws.amazon.com/blogs/architecture/optimizing-your-aws-infrastructure-for-sustainability-part-ii-storage/)
**Related videos:**
+ [Building Sustainably on AWS](https://www.youtube.com/watch?v=ARAitMSIxc8)
# SUS02-BP04 Optimize geographic placement of workloads for user locations
Analyze network access patterns to identify where your customers are connecting from geographically. Select Regions and services that reduce the distance network traffic must travel to decrease the total network resources required to support your workload.
** Common anti-patterns: **
+ You select the workload's Region based on your own location.
**Benefits of establishing this best practice:** Placing a workload close to its customers provides the lowest latency while decreasing data movement across the network and lowering environmental impact.
**Level of risk exposed if this best practice is not established:** Medium
## Implementation guidance
+ Select the Regions for your workload deployment based on the following key elements:
+ **Your Sustainability goal:** as explained in [Region selection](https://docs.aws.amazon.com/wellarchitected/latest/sustainability-pillar/region-selection.html).
+ **Where your data is located:** For data-heavy applications (such as big data and machine learning), application code should execute as close to the data as possible.
+ **Where your users are located:** For user-facing applications, choose a Region close to your workload’s customer base.
+ **Other constraints:** Consider constraints such as security and compliance as explained in [What to Consider when Selecting a Region for your Workloads](https://aws.amazon.com/blogs/architecture/what-to-consider-when-selecting-a-region-for-your-workloads/).
+ Use [AWS Local Zones](https://aws.amazon.com/about-aws/global-infrastructure/localzones/) to run workloads like video rendering and graphics-intensive virtual desktop applications. Local Zones allow you to benefit from having compute and storage resources closer to end users.
+ Use local caching or [AWS Caching Solutions](https://aws.amazon.com/caching/aws-caching/) for frequently used resources to improve performance, reduce data movement, and lower environmental impact.
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2022-03-31/framework/sus_sus_user_a5.html)
+ Use services that can help you run code closer to users of your workload:
[\[See the AWS documentation website for more details\]](http://docs.aws.amazon.com/wellarchitected/2022-03-31/framework/sus_sus_user_a5.html)
+ Use connection pooling to enable connection reuse, and reduce required resources.
+ Use distributed data stores that don’t rely on persistent connections and synchronous updates for consistency to serve regional populations.
+ Replace pre-provisioned static network capacity with shared dynamic capacity, and share the sustainability impact of network capacity with other subscribers.
## Resources
**Related documents:**
+ [Optimizing your AWS Infrastructure for Sustainability, Part III: Networking](https://aws.amazon.com/blogs/architecture/optimizing-your-aws-infrastructure-for-sustainability-part-iii-networking/)
+ [Amazon ElastiCache Documentation](https://docs.aws.amazon.com/elasticache/index.html)
+ [What is Amazon CloudFront?](https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/Introduction.html)
+ [Amazon CloudFront Key Features](https://aws.amazon.com/cloudfront/features/)
+ [Lambda@Edge](https://aws.amazon.com/lambda/edge/)
+ [CloudFront Functions](https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/cloudfront-functions.html)
+ [AWS IoT Greengrass](https://aws.amazon.com/greengrass/)
**Related videos:**
+ [Building Sustainably on AWS](https://www.youtube.com/watch?v=ARAitMSIxc8)
**Related examples:**
+ [AWS Networking Workshops](https://catalog.workshops.aws/networking/en-US)
# SUS02-BP05 Optimize team member resources for activities performed
Optimize resources provided to team members to minimize the sustainability impact while supporting their needs. For example, perform complex operations, such as rendering and compilation, on highly utilized shared cloud desktops instead of on underutilized high-powered single-user systems.
**Level of risk exposed if this best practice is not established:** Low
## Implementation guidance
+ Provision workstations and other devices to align with how they’re used.
+ Use virtual desktops and application streaming to limit upgrade and device requirements.
+ Move processor or memory-intensive tasks to the cloud.
+ Evaluate the impact of processes and systems on your device lifecycle, and select solutions that minimize the requirement for device replacement while satisfying business requirements.
+ Implement remote management for devices to reduce required business travel.
## Resources
**Related documents:**
+ [What is Amazon WorkSpaces?](https://docs.aws.amazon.com/workspaces/latest/adminguide/amazon-workspaces.html)
+ [Amazon AppStream 2.0 Documentation](https://docs.aws.amazon.com/appstream2/)
+ [NICE DCV](https://docs.aws.amazon.com/dcv/)
+ [AWS Systems Manager Fleet Manager](https://docs.aws.amazon.com/systems-manager/latest/userguide/fleet.html)
**Related videos:**
+ [Building Sustainably on AWS](https://www.youtube.com/watch?v=ARAitMSIxc8)