Scale your compute resources dynamically

The ability to dynamically scale compute resources is crucial for maintaining performance efficiency. This approach not only saves costs by preventing over-provisioning but also ensures that workloads run optimally under varying demand. Leveraging cloud elasticity allows for real-time adjustments that meet workload requirements without sacrificing performance.

Best Practices

• Use Auto Scaling Groups: Implementing Auto Scaling Groups helps manage EC2 instances automatically. It adjusts the number of running instances in response to traffic loads, ensuring sufficient resources during peak times and scaling down during low demand to minimize costs.

Supporting Questions

• Are your compute resources automatically scaling based on real-time usage?

Roles and Responsibilities

• Cloud Architect: The Cloud Architect is responsible for designing cloud solutions that effectively utilize dynamic scaling and ensures that the architecture can adapt to workload changes.

Artifacts

• Auto Scaling Configuration: A document that outlines the settings and policies for auto-scaling, including threshold metrics, scaling actions, and the target utilization levels.

Cloud Services

AWS

• Amazon EC2: Amazon EC2 provides resizable compute capacity in the cloud. It allows you to scale your compute resources up or down dynamically based on demand through features like Auto Scaling.
• AWS Lambda: AWS Lambda lets you run code without provisioning or managing servers, automatically scaling in response to your application’s needs, which is ideal for workloads with variable compute demands.

Question: How do you select and use compute resources in your workload?
Pillar: Performance Efficiency (Code: PERF)