SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company runs a containerized microservices application on Amazon ECS with Fargate launch type. The application consists of a frontend service and a backend service. The backend service is CPU-intensive and experiences high load during business hours. The operations team observes that the frontend service sometimes returns 503 errors during peak load. The team has already configured an ECS service auto scaling policy for the backend service based on average CPU utilization with a target value of 70%. The backend service is currently running 4 tasks, and the frontend is running 2 tasks. The errors seem to correlate with the backend scaling up. Which solution should the team implement to improve the application's performance and reduce errors?
⚠ Common exam trap
Watch out — candidates often assume the solution is to scale earlier (Option B) or add more frontend capacity (Option D), when the real issue is the instability during the scaling event itself, which is addressed by stabilizing the scaling process with step policies and cooldowns.
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
✓
Update the backend service auto scaling policy to use a combination of CPU and memory utilization metrics with a step scaling policy, and increase the cooldown period to allow tasks to stabilize before additional scaling actions.
The 503 errors during backend scale-up are likely caused by the backend tasks not being fully ready to handle traffic immediately after launch. By using a combination of CPU and memory utilization metrics with a step scaling policy, the team can make scaling decisions more responsive to actual load patterns. Increasing the cooldown period prevents additional scaling actions from being triggered prematurely, giving new tasks time to stabilize and reducing the window where the backend is overwhelmed, which in turn reduces frontend timeouts.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Update the backend service auto scaling policy to use a combination of CPU and memory utilization metrics with a step scaling policy, and increase the cooldown period to allow tasks to stabilize before additional scaling actions.
Why this is correct
Multiple metrics and step scaling with proper cooldown prevent premature scaling and handle spikes better.
- ✗
Reduce the target CPU utilization for the backend auto scaling policy from 70% to 50% to trigger scaling earlier and keep CPU lower.
Why it's wrong here
Lower threshold might cause more frequent scaling but doesn't address the root cause of errors during scaling events.
- ✗
Change the backend service from Fargate to EC2 launch type and use larger instance types to provide more CPU capacity.
Why it's wrong here
Fargate abstracts instances; changing launch type is unnecessary. CPU can be increased by increasing task size.
- ✗
Increase the desired count of the frontend service to 4 tasks to handle more requests and reduce the load on the backend service.
Why it's wrong here
Frontend tasks do not reduce backend CPU load; the backend is the bottleneck.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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