EC2 Auto Scaling Based on CloudWatch Metrics
A travel booking site uses EC2 instances behind an ALB. CPU is consistently high during peak traffic, and request latency rises. What should be configured?
Quick Answer
An Auto Scaling policy tied to a CloudWatch metric like CPU utilization or request latency is the right fix because it closes the loop between the actual symptom, rising CPU and climbing latency under peak load, and the response, adding capacity automatically when that symptom appears. Without it, a fixed number of EC2 instances behind the ALB has to absorb all of the peak traffic on its own, so per-instance CPU climbs and each request takes longer to process, which is exactly the pattern described. By scaling out when the chosen metric crosses a threshold, the same peak traffic gets spread across more instances, which brings per-instance CPU back down and lets requests get processed with lower latency, and then scaling back in once traffic subsides keeps costs from staying elevated outside of peak hours. This is more directly targeted than something like simply resizing the instances to a larger type, since a static larger fleet still wouldn't adapt as traffic continues to vary, while a scaling policy handles both today's peak and future growth without needing to be manually resized again. Whenever a scenario shows a fixed-capacity fleet behind a load balancer with CPU and latency both degrading specifically during peak traffic, that load-driven pattern is the signal to reach for a CloudWatch-metric-based Auto Scaling policy rather than a one-time capacity change.
⚠ Common exam trap
Many exam-takers confuse monitoring (VPC endpoints) or data protection (S3 Object Lock) with scaling solutions, or think disabling health checks reduces overhead, when the correct approach is to scale horizontally based on load metrics.
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
✓
Auto Scaling policy based on an appropriate CloudWatch metric
An Auto Scaling policy based on a CloudWatch metric like CPUUtilization or request latency directly addresses the root cause: rising CPU and latency under peak traffic. By automatically adding EC2 instances when the metric breaches a threshold, the ALB can distribute load across more resources, reducing CPU per instance and improving response times. This is the standard AWS solution for dynamic scaling to maintain performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A VPC endpoint for CloudWatch only
Why it's wrong here
A VPC endpoint changes network path, not instance capacity.
- ✓
Auto Scaling policy based on an appropriate CloudWatch metric
Why this is correct
Auto Scaling adds capacity when load increases and removes it when load falls.
- ✗
S3 Object Lock
Why it's wrong here
Object Lock controls retention, not EC2 compute capacity.
- ✗
Disable health checks
Why it's wrong here
Disabling health checks weakens availability and does not improve capacity.
Go deeper
Related to this question
About these practice questions
One of 302 original SAA-C03 practice questions on Courseiva, each with a full explanation and wrong-answer analysis — not exam dumps or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
3 more ways this is tested on SAA-C03
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A travel booking site uses EC2 instances behind an ALB. CPU is consistently high during peak traffic, and request latency rises. What should be configured? The design must avoid adding custom operational scripts.
easy- A.A VPC endpoint for CloudWatch only
- ✓ B.Auto Scaling policy based on an appropriate CloudWatch metric
- C.S3 Object Lock
- D.Disable health checks
Why B: An Auto Scaling policy based on a CloudWatch metric like CPUUtilization or request latency directly addresses the high CPU and rising latency by automatically adding EC2 instances during peak traffic. This eliminates the need for custom scripts and ensures the application scales horizontally to maintain performance.
Variation 2. A travel booking site uses EC2 instances behind an ALB. CPU is consistently high during peak traffic, and request latency rises. What should be configured? The architecture review board prefers a managed AWS-native control.
easy- A.A VPC endpoint for CloudWatch only
- ✓ B.Auto Scaling policy based on an appropriate CloudWatch metric
- C.S3 Object Lock
- D.Disable health checks
Why B: An Auto Scaling policy based on an appropriate CloudWatch metric (such as CPUUtilization or request latency) dynamically adds or removes EC2 instances to match demand. This managed AWS-native control directly addresses high CPU and rising latency during peak traffic by scaling out capacity, which is the preferred approach per the architecture review board's requirement for a managed solution.
Variation 3. A retail API uses EC2 instances behind an ALB. CPU is consistently high during peak traffic, and request latency rises. What should be configured? The design must avoid adding custom operational scripts.
easy- ✓ A.Auto Scaling policy based on an appropriate CloudWatch metric
- B.S3 Object Lock
- C.A VPC endpoint for CloudWatch only
- D.Disable health checks
Why A: An Auto Scaling policy based on a CloudWatch metric like CPUUtilization or ALB TargetResponseTime can dynamically add or remove EC2 instances to match demand. This directly addresses the high CPU and rising latency during peak traffic without requiring custom scripts, as the scaling actions are fully managed by AWS. The ALB distributes traffic across the scaled instances, reducing per-instance load and improving response times.
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This SAA-C03 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the SAA-C03 exam.