DOP-C02 Resilient Cloud Solutions Practice Question
A company runs a critical web application on Amazon EC2 instances behind an Application Load Balancer (ALB). The application frequently experiences high latency during peak hours. The DevOps team needs to implement a solution that automatically adds capacity based on demand and reduces cost during off-peak hours. Which combination of AWS services should the team use?
⚠ Common exam trap
Candidates often choose scheduled scaling (Option A) because it seems straightforward for known peak hours, but they overlook the requirement to handle unpredictable high latency during peak hours, which demands a dynamic, metric-based scaling solution like target tracking.
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
✓
Use an AWS Auto Scaling group with target tracking scaling policies based on the ALB's request count per target, and attach it to the ALB target group.
Target tracking scaling policies allow the Auto Scaling group to automatically adjust capacity based on a specific metric, such as ALB request count per target, which directly reflects the load on each instance. This ensures that capacity is added during high latency periods and removed during off-peak hours, optimizing both performance and cost. The ALB target group integration ensures that new instances are automatically registered and start receiving traffic.
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 an AWS Auto Scaling group with scheduled scaling policies that add instances during known peak hours and remove them during off-peak hours.
Why it's wrong here
This approach only adjusts capacity on a predetermined time schedule, so it cannot react to unexpected traffic spikes or sudden drops in demand. A critical web application often experiences unpredictable load patterns, and during off-peak hours a flash crowd would still find the fleet undersized. Scheduled scaling is best for predictable baselines but lacks the dynamic feedback loop needed for real-time elasticity.
- ✗
Implement Amazon Route 53 weighted routing policies to distribute traffic to multiple ALBs, each fronting a fixed set of EC2 instances.
Why it's wrong here
Weighted routing only splits DNS traffic between fixed ALB fleets; it does not automatically add or remove EC2 capacity in response to load. If one target group becomes saturated, the policy continues sending a fixed share of requests there, potentially causing overload, while other instances sit idle. This solution requires manual reconfiguration or separate scaling mechanisms, and it does not leverage ALB target-group health or utilization signals to drive capacity changes.
- ✗
Use an AWS Auto Scaling group with simple scaling policies based on CPU utilization and attach it to the ALB target group.
Why it's wrong here
Simple scaling policies react only after a CloudWatch alarm breaches, and the cooldown period that follows prevents rapid successive adjustments, making it slow for sudden spikes. CPU utilization is a host-level proxy that does not directly reflect application request load, so the metric can spike quickly or lag behind actual demand. Target tracking provides a smoother, metric-driven control loop that continuously calculates required capacity, which is more effective for the bursty traffic described.
- ✓
Use an AWS Auto Scaling group with target tracking scaling policies based on the ALB's request count per target, and attach it to the ALB target group.
Why this is correct
This configuration uses the ALB's per-target request count as a scaling metric, so Auto Scaling continuously adjusts the EC2 fleet to keep that value near the chosen target. The ALB target group integration ensures newly launched instances are immediately registered to receive traffic, and the policy can scale both out and in based on real observed load. It is designed for variable workloads like critical web apps and responds faster and more accurately than scheduled or simple scaling policies.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DOP-C02 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 DOP-C02 exam.