SAP-C02 Design for New Solutions Practice Question
A company runs a high-traffic web application on Amazon EC2 instances behind an Application Load Balancer. The application experiences intermittent latency spikes during peak hours. Analysis shows that the latency spikes correlate with high CPU utilization on the EC2 instances. The company wants to reduce latency without over-provisioning. Which solution is MOST cost-effective and scalable?
⚠ Common exam trap
Candidates often confuse addressing the symptom (high CPU) with vertical scaling (Option C) or cost-saving measures (Option B), rather than recognizing that horizontal auto-scaling with a target tracking policy is the most cost-effective and scalable solution for handling intermittent latency spikes caused by CPU utilization.
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
✓
Configure an Auto Scaling group with a target tracking scaling policy based on average CPU utilization.
A target tracking scaling policy based on average CPU utilization automatically adjusts the number of EC2 instances in the Auto Scaling group to maintain a target CPU utilization level. This directly addresses the latency spikes caused by high CPU utilization during peak hours by scaling out horizontally, while scaling in during low traffic to avoid over-provisioning, making it both cost-effective and scalable.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add Amazon ElastiCache to cache database queries.
Why it's wrong here
This addresses database latency, not compute CPU utilization.
- ✗
Use Spot Instances to reduce costs and scale horizontally.
Why it's wrong here
Spot Instances can be interrupted, which may cause latency issues.
- ✗
Increase the EC2 instance size to handle peak loads.
Why it's wrong here
This leads to over-provisioning and higher costs.
- ✓
Configure an Auto Scaling group with a target tracking scaling policy based on average CPU utilization.
Why this is correct
This dynamically adjusts capacity to maintain target utilization, optimizing cost and performance.
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