The answer is that the auto scaling is not working because the ECS Fargate service has already reached the maximum task limit of 10 defined in the auto scaling configuration. Even though the target tracking scaling policy is set to a 50% CPU target and actual utilization is at 70%, the scaling policy cannot trigger a scale-out event because it is blocked by the hard cap on the maximum number of tasks. This scenario tests your understanding of how ECS Service Auto Scaling respects the min/max boundaries, a common pitfall on the AWS Certified DevOps Engineer Professional DOP-C02 exam where engineers often overlook that a scaling policy cannot exceed the configured maximum. The fix is straightforward: increase the maximum tasks in the auto scaling configuration to allow further scale-out. Remember the trap: a scaling policy can only request tasks within the range you set—if you hit the max, scaling stops regardless of demand. Memory tip: “Max tasks = scaling ceiling; hit it, and your policy is just a wish.”
DOP-C02 Incident and Event Response Practice Question
This DOP-C02 practice question tests your understanding of incident and event response. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. 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 company runs a microservices application on Amazon ECS with Fargate. The application includes a service that processes messages from an Amazon SQS queue. Recently, the processing time has increased, and the SQS queue depth is growing. The CloudWatch metrics show that the ECS service's CPU utilization is consistently around 70%, memory utilization is 80%, and the number of running tasks is at the maximum allowed (10). The service is configured with a target tracking scaling policy based on CPU utilization with a target value of 50%. However, the auto scaling does not seem to be adding tasks. The engineer checks the ECS service events and finds no scaling activity. What is the MOST likely reason the auto scaling is not working, and what action should be taken to resolve the issue?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The service has reached the maximum number of tasks defined in the auto scaling configuration; increase the maximum tasks.
The auto scaling is not adding tasks because the ECS service has already reached the maximum number of tasks defined in the auto scaling configuration (10). With CPU utilization at 70% and the target tracking policy set to 50%, the policy would normally trigger scale-out actions, but since the maximum task count is already hit, no scaling activity occurs. The engineer must increase the maximum tasks in the auto scaling configuration to allow further scale-out.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
The service has reached the maximum number of tasks defined in the auto scaling configuration; increase the maximum tasks.
Why this is correct
The max tasks is 10 and the service is at 10, so scaling cannot occur. Increasing the max allows scaling.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The scaling policy is not properly configured; recreate it with a lower target value.
Why it's wrong here
The policy is configured and the metric is above target, but scaling is blocked by the max.
✗
The CloudWatch metric is not being emitted correctly; check the metric namespace.
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may assume the scaling policy itself is misconfigured or that Fargate lacks support for target tracking, when in reality the issue is the hard cap on the maximum number of tasks preventing any scale-out action.
Trap categories for this question
Command / output trap
The metric is showing, so it is being emitted.
Detailed technical explanation
How to think about this question
Target tracking scaling policies in ECS work by creating CloudWatch alarms that monitor the specified metric (e.g., CPU utilization) and adjust the desired count of tasks. When the desired count equals the maximum task count, the policy cannot increase further, and scaling activity stops. This is a common pitfall where operators forget to set an adequate maximum task limit, especially under variable load. In production, it's critical to monitor the 'ServiceAutoScalingMaxCapacity' and set it based on peak load estimates.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
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
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Incident and Event Response — This question tests Incident and Event Response — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The service has reached the maximum number of tasks defined in the auto scaling configuration; increase the maximum tasks. — The auto scaling is not adding tasks because the ECS service has already reached the maximum number of tasks defined in the auto scaling configuration (10). With CPU utilization at 70% and the target tracking policy set to 50%, the policy would normally trigger scale-out actions, but since the maximum task count is already hit, no scaling activity occurs. The engineer must increase the maximum tasks in the auto scaling configuration to allow further scale-out.
What should I do if I get this DOP-C02 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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