Search for Well Architected Advice
< All Topics
Print

Obtain resources upon detection of impairment to a workload

The ability to scale resources reactively is critical for maintaining availability in a cloud environment. This approach ensures that, when issues arise, the system can respond swiftly—thus minimizing downtime and user impact.

Best Practices

  • Automated Scaling Policies: Implement automated scaling policies based on metrics such as CPU usage, memory, or custom metrics. This proactive measure enables your resources to automatically adjust, preserving workload performance and availability.

Supporting Questions

  • Do you have monitoring in place to detect when workloads are underperforming?
  • Have you configured alerts to notify your team of resource impairments?

Roles and Responsibilities

  • DevOps Engineer: Responsible for designing and implementing automated scaling solutions, ensuring the workload can autonomously respond to changing demand and any impairments.

Artifacts

  • CloudFormation Templates: Utilize CloudFormation templates to manage your infrastructure as code, allowing you to define and deploy scaling policies and resource configurations consistently.

Cloud Services

AWS

  • Amazon EC2 Auto Scaling: EC2 Auto Scaling allows you to increase or decrease the number of EC2 instances as demand changes, ensuring the application remains available with optimal resource usage.
  • AWS Lambda: AWS Lambda automatically scales the number of concurrent requests to your application, providing a serverless option that adjusts seamlessly to varying loads.

Question: How do you design your workload to adapt to changes in demand?
Pillar: Reliability (Code: REL)

Table of Contents