- A
Monitor CPU and memory utilization metrics in CloudWatch; increase the task size (CPU and memory) in the task definition.
Monitor CPU and memory utilization in CloudWatch to detect resource exhaustion. Increasing task size (CPU and memory) provides more resources per task, preventing OOM or CPU throttling without changing task count.
- B
Set up CloudWatch Logs for the application and check for out-of-memory errors; then increase the number of tasks.
Why wrong: CloudWatch Logs can show out-of-memory errors, but increasing the number of tasks does not address insufficient resources per task; it may spread load but not fix the root cause if tasks still have inadequate resources.
- C
Monitor NetworkPacketsIn and NetworkPacketsOut metrics in CloudWatch; increase the number of tasks.
Why wrong: NetworkPacketsIn/Out measure network traffic, not resource exhaustion. Increasing task count might help with network load but does not directly address CPU/memory exhaustion.
- D
Monitor the ALB error metrics (5xx count) and scale the ECS service based on request count.
Why wrong: ALB 5xx errors indicate failures but not specifically resource exhaustion. Scaling based on request count addresses load but not per-task resource limits; the underlying task definition may still be undersized.
DOP-C02 Incident and Event Response Practice Question
This DOP-C02 practice question tests your understanding of incident and event response. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 critical application on Amazon ECS with Fargate. The application is deployed across multiple Availability Zones and uses an Application Load Balancer (ALB) as the front-end. During a recent incident, users experienced intermittent connectivity failures. The DevOps team suspects that tasks are being stopped due to resource exhaustion. Which combination of metrics and actions should the team use to diagnose and prevent recurrence?
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
Monitor CPU and memory utilization metrics in CloudWatch; increase the task size (CPU and memory) in the task definition.
Option A is correct because CPU and memory utilization metrics in CloudWatch directly indicate resource exhaustion, which is the suspected cause of tasks being stopped. Increasing the task size (CPU and memory) in the task definition provides more resources per task, preventing the OOM killer or CPU throttling from stopping tasks, without changing the number of tasks or scaling logic.
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.
- ✓
Monitor CPU and memory utilization metrics in CloudWatch; increase the task size (CPU and memory) in the task definition.
Why this is correct
Monitor CPU and memory utilization in CloudWatch to detect resource exhaustion. Increasing task size (CPU and memory) provides more resources per task, preventing OOM or CPU throttling without changing task count.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set up CloudWatch Logs for the application and check for out-of-memory errors; then increase the number of tasks.
Why it's wrong here
CloudWatch Logs can show out-of-memory errors, but increasing the number of tasks does not address insufficient resources per task; it may spread load but not fix the root cause if tasks still have inadequate resources.
- ✗
Monitor NetworkPacketsIn and NetworkPacketsOut metrics in CloudWatch; increase the number of tasks.
Why it's wrong here
NetworkPacketsIn/Out measure network traffic, not resource exhaustion. Increasing task count might help with network load but does not directly address CPU/memory exhaustion.
- ✗
Monitor the ALB error metrics (5xx count) and scale the ECS service based on request count.
Why it's wrong here
ALB 5xx errors indicate failures but not specifically resource exhaustion. Scaling based on request count addresses load but not per-task resource limits; the underlying task definition may still be undersized.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse horizontal scaling (increasing task count) with vertical scaling (increasing task size), assuming that adding more tasks resolves resource exhaustion when the actual issue is insufficient resources per task.
Trap categories for this question
Command / output trap
CloudWatch Logs can show out-of-memory errors, but increasing the number of tasks does not address insufficient resources per task; it may spread load but not fix the root cause if tasks still have inadequate resources.
Detailed technical explanation
How to think about this question
Under the hood, ECS with Fargate enforces hard limits on CPU and memory at the task level; when a task exceeds its allocated memory, the Linux kernel's Out-Of-Memory (OOM) killer terminates the container, and CPU throttling occurs if the task exceeds its CPU limit. CloudWatch metrics like `MemoryUtilized` and `CPUUtilization` are collected at 1-minute granularity, and sustained high values (e.g., >80%) indicate the need for a larger task size rather than horizontal scaling, which would only spread the load without fixing per-task starvation.
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.
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FAQ
Questions learners often ask
What does this DOP-C02 question test?
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: Monitor CPU and memory utilization metrics in CloudWatch; increase the task size (CPU and memory) in the task definition. — Option A is correct because CPU and memory utilization metrics in CloudWatch directly indicate resource exhaustion, which is the suspected cause of tasks being stopped. Increasing the task size (CPU and memory) in the task definition provides more resources per task, preventing the OOM killer or CPU throttling from stopping tasks, without changing the number of tasks or scaling logic.
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 11, 2026
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