A company runs an application on Amazon EC2 instances. The EC2 instances are in an Auto Scaling group and run behind an Application Load Balancer (ALB). The application experiences errors when total…

Question

Options

• AUse the ALB's RequestCount metric. Configure a time range of 2 weeks and a period of 1 minute.
• BUse Amazon CloudWatch metric math to generate a sum of request counts for all the EC2
• CCreate Amazon CloudWatch custom metrics on the EC2 launch configuration templates to create
• DCreate an Amazon EventBridge (Amazon CloudWatch Events) rule. Configure an EC2 event

• A
  89% (25)
• B
  7% (2)
• C
  4% (1)

Explanation

Option A is correct because the ALB natively publishes a RequestCount metric to Amazon CloudWatch, which counts every request processed by the load balancer - making it the most direct and accurate way to measure total incoming requests. Setting a 2-week time range with a 1-minute period gives granular visibility into when the 100 req/s threshold was breached.

Why the distractors are wrong:

• B is wrong because measuring request counts at the EC2 instance level via metric math is indirect, error-prone, and misses requests that may be rejected before reaching an instance (e.g., by the ALB itself).
• C is wrong because launch configuration templates are for provisioning EC2 instances - they have no mechanism to emit request-count metrics; custom CloudWatch metrics require application-level instrumentation, not launch templates.
• D is wrong because EventBridge/CloudWatch Events rules respond to state change events (e.g., instance started/stopped), not continuous request-rate metrics - this would not capture request counts at all.

Memory tip: Think "measure at the front door" - the ALB sits at the entry point of all traffic, so its RequestCount metric is always the authoritative source for total request volume, just like a turnstile at a stadium entrance counts every person regardless of where they go inside.

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