SUS02 - How do you take advantage of user behavior patterns to support your sustainability goals?
Best Practices
Best Practices
This question includes the following best practices:
- SUS02-BP01: Scale workload infrastructure dynamically
- SUS02-BP02: Align SLAs with sustainability goals
- SUS02-BP03: Stop the creation and maintenance of unused assets
- SUS02-BP04: Optimize geographic placement of workloads based on their networking requirements
- SUS02-BP05: Optimize team member resources for activities performed
- SUS02-BP06: Implement buffering or throttling to flatten the demand curve
Key Concepts
Sustainability Design Foundations
Demand pattern analysis: Use this concept to guide architecture and operating decisions for this question area. Define measurable targets, assign clear ownership, and review results regularly against expected business outcomes.
Usage shaping: Use this concept to guide architecture and operating decisions for this question area. Define measurable targets, assign clear ownership, and review results regularly against expected business outcomes.
Experience-aware efficiency: Use this concept to guide architecture and operating decisions for this question area. Define measurable targets, assign clear ownership, and review results regularly against expected business outcomes.
Operational Sustainability Controls
Peak management: Use this concept to guide architecture and operating decisions for this question area. Define measurable targets, assign clear ownership, and review results regularly against expected business outcomes.
Behavior-informed design: Use this concept to guide architecture and operating decisions for this question area. Define measurable targets, assign clear ownership, and review results regularly against expected business outcomes.
Feedback loops: Use this concept to guide architecture and operating decisions for this question area. Define measurable targets, assign clear ownership, and review results regularly against expected business outcomes.
Implementation Approach
1. Analyze behavior data
- Identify temporal demand peaks and idle periods
- Segment users by access behavior and geography
- Map high-cost interactions to user journeys
- Set sustainability KPIs linked to usage patterns
2. Design for efficient consumption
- Cache high-frequency content and API responses
- Optimize payload sizes and request frequency
- Schedule non-urgent operations during off-peak windows
- Implement adaptive quality or batching strategies
3. Align capacity with behavior
- Configure autoscaling around observed patterns
- Pre-scale only when demand signals justify it
- Throttle or queue non-critical workloads during peaks
- Expose product levers that encourage efficient usage
4. Measure and improve
- Monitor per-journey resource intensity
- Run experiments on UX changes that reduce waste
- Review outcomes with product and engineering teams
- Scale successful pattern-based optimizations
AWS Services to Consider
Amazon CloudWatch
Collects metrics, logs, alarms, and dashboards so teams can detect issues early and track operational outcomes.
Amazon CloudFront
Caches content at edge locations to reduce latency for global users and offload origins.
Amazon SQS
Buffers asynchronous workloads to absorb traffic spikes and improve throughput stability.
AWS Lambda
Runs event-driven code without managing servers, ideal for automation and on-demand operational workflows.
Amazon Athena
Runs serverless SQL queries on data in S3 for analytics and operational reporting.
Common Challenges and Solutions
Challenge: Limited visibility into behavior-driven load
Solution: Instrument user journeys and correlate behavior metrics with infrastructure utilization.
Challenge: Capacity planned for worst case all the time
Solution: Adopt elastic scaling and queue-based smoothing for bursty non-critical work.
Challenge: Efficiency changes degrade UX
Solution: A/B test optimization changes and retain only those that preserve user outcomes.