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Continuous Improvement for Existing SolutionseasyMultiple ChoiceObjective-mapped

SAP-C02 Continuous Improvement for Existing Solutions Practice Question

A company runs a web application on EC2 instances behind an Application Load Balancer (ALB). The application experiences periodic spikes in traffic. The operations team wants to ensure that the application can handle the spikes without manual intervention. What is the MOST cost-effective solution?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Create a target tracking scaling policy using the ALB RequestCountPerTarget metric.

A target tracking scaling policy automatically adjusts capacity based on a specific metric, and using the ALB RequestCountPerTarget metric is appropriate for handling traffic spikes in a cost-effective manner. This policy maintains the desired metric value by adding or removing instances as needed, without manual intervention. Option A is incorrect because a scheduled scaling policy assumes predictable peaks, but the traffic spikes are periodic and may not follow a fixed schedule. Option C is incorrect because manual intervention is not cost-effective and defeats the purpose of automation. Option D is incorrect because a simple scaling policy based on CPU utilization may not react quickly enough to sudden traffic spikes and could be less cost-effective than target tracking.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use a scheduled scaling policy to add instances during predicted peak hours.

    Why it's wrong here

    Does not handle unpredictable spikes.

  • Create a target tracking scaling policy using the ALB RequestCountPerTarget metric.

    Why this is correct

    This automatically scales based on request count per target.

  • Manually add instances when traffic spikes are expected.

    Why it's wrong here

    Manual intervention is not automated.

  • Use a simple scaling policy based on CPU utilization.

    Why it's wrong here

    CPU might not correlate directly with request spikes.

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