AWS Certified Solutions Architect – Associate (SAA-C02) — Question 384

An ecommerce website is deploying its web application as Amazon Elastic Container Service (Amazon ECS) container instances behind an Application Load
Balancer (ALB). During periods of high activity, the website slows down and availability is reduced. A solutions architect uses Amazon CloudWatch alarms to receive notifications whenever there is an availability issue so they can scale out resources. Company management wants a solution that automatically responds to such events.
Which solution meets these requirements?

Answer options

• A. Set up AWS Auto Scaling to scale out the ECS service when there are timeouts on the ALB. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
• B. Set up AWS Auto Scaling to scale out the ECS service when the ALB CPU utilization is too high. Setup AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
• C. Set up AWS Auto Scaling to scale out the ECS service when the service's CPU utilization is too high. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.
• D. Set up AWS Auto Scaling to scale out the ECS service when the ALB target group CPU utilization is too high. Set up AWS Auto Scaling to scale out the ECS cluster when the CPU or memory reservation is too high.

Correct answer: C

Explanation

Option C is correct because scaling an ECS service is best triggered by the service's own CPU utilization, which indicates the actual load on the container tasks. Concurrently, the underlying ECS cluster must be scaled based on CPU or memory reservation to ensure there is sufficient EC2 instance capacity to launch the newly scaled-out tasks. Other options are incorrect because ALBs and target groups do not have CPU utilization metrics, and scaling based on ALB timeouts is not a standard or reliable metric for auto-scaling.