The answer is an Auto Scaling policy based on an appropriate CloudWatch metric. This is correct because when a retail API behind an ALB experiences sustained high CPU and rising latency, a dynamic scaling policy tied to metrics like CPUUtilization or ALB RequestCountPerTarget automatically adds or removes EC2 instances to match real-time demand, preventing performance degradation without manual intervention. On the SAA-C03 exam, this scenario tests your understanding of managed, AWS-native controls for elasticity—a common trap is choosing a scheduled scaling policy or a manual instance resize, which fail to react to unpredictable traffic spikes. Remember that CloudWatch metrics drive the scaling action, not static thresholds alone. A useful memory tip: “CPU and latency climb? Let CloudWatch metrics define the climb.”
SAA-C03 Design High-Performing Architectures Practice Question
This SAA-C03 practice question tests your understanding of design high-performing architectures. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. A key principle to apply: aWS Auto Scaling dynamically adjusts EC2 instance count.. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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 architecture review board prefers a managed AWS-native control.
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
The correct answer is A because an Auto Scaling policy based on an appropriate CloudWatch metric (e.g., CPUUtilization or ALB RequestCountPerTarget) dynamically adds or removes EC2 instances to match demand, preventing sustained high CPU and rising latency. This is a managed, AWS-native control that aligns with the architecture review board's preference.
Key principle: AWS Auto Scaling dynamically adjusts EC2 instance count.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
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.
Related concept
AWS Auto Scaling dynamically adjusts EC2 instance count.
✗
S3 Object Lock
Why it's wrong here
Object Lock controls retention, not EC2 compute capacity.
✗
A VPC endpoint for CloudWatch only
Why it's wrong here
A VPC endpoint changes network path, not instance capacity.
✗
Disable health checks
Why it's wrong here
Disabling health checks weakens availability and does not improve capacity.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse operational controls (like health checks or VPC endpoints) with scaling mechanisms, or assume that disabling health checks somehow improves performance, when in fact it worsens reliability and latency.
Detailed technical explanation
How to think about this question
Under the hood, the Auto Scaling group uses a target tracking scaling policy that adjusts the desired capacity based on a CloudWatch alarm (e.g., CPUUtilization > 70% for 5 minutes). The ALB distributes traffic to healthy instances via round-robin, and scaling out reduces per-instance CPU load, lowering latency. In a real-world scenario, a sudden flash sale could spike CPU; without Auto Scaling, latency would degrade user experience, but with it, new instances are launched and registered with the ALB within minutes.
KKey Concepts to Remember
AWS Auto Scaling dynamically adjusts EC2 instance count.
Auto Scaling policies use CloudWatch metrics like CPU utilization.
It adds capacity during high demand and removes it during low demand.
Auto Scaling integrates with ALBs to distribute traffic across instances.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
AWS Auto Scaling dynamically adjusts EC2 instance count.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
What to study next
Got this wrong? Here's your next step.
Review aWS Auto Scaling dynamically adjusts EC2 instance count., then practise related SAA-C03 questions on the same topic to reinforce the concept.
Design High-Performing Architectures — This question tests Design High-Performing Architectures — AWS Auto Scaling dynamically adjusts EC2 instance count..
What is the correct answer to this question?
The correct answer is: Auto Scaling policy based on an appropriate CloudWatch metric — The correct answer is A because an Auto Scaling policy based on an appropriate CloudWatch metric (e.g., CPUUtilization or ALB RequestCountPerTarget) dynamically adds or removes EC2 instances to match demand, preventing sustained high CPU and rising latency. This is a managed, AWS-native control that aligns with the architecture review board's preference.
What should I do if I get this SAA-C03 question wrong?
Review aWS Auto Scaling dynamically adjusts EC2 instance count., then practise related SAA-C03 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
AWS Auto Scaling dynamically adjusts EC2 instance count.
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Variation 1. A retail API uses EC2 instances behind an ALB. CPU is consistently high during peak traffic, and request latency rises. What should be configured?
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 an appropriate CloudWatch metric (such as CPUUtilization or ALBRequestCountPerTarget) dynamically adds or removes EC2 instances to match demand. This directly addresses the high CPU and rising latency by distributing the load across more instances, preventing performance degradation during peak traffic.
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Question Discussion
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