- A
Use AWS Auto Scaling to scale the ECS service based on the custom metric.
Why wrong: AWS Auto Scaling is not directly used for ECS Service Auto Scaling; Application Auto Scaling is used.
- B
Create a CloudWatch dashboard to visualize the metric and manually adjust the service count.
Why wrong: Manual intervention is not automated scaling.
- C
Publish the custom metric to Amazon CloudWatch, then create a target tracking scaling policy in Application Auto Scaling for the ECS service.
This is the recommended approach for scaling ECS services using custom metrics.
- D
Use an AWS Lambda function to directly update the desired count of the ECS service based on the metric.
Why wrong: Lambda can be used but it is not a best practice; CloudWatch and Application Auto Scaling provide a native solution.
DOP-C02 Monitoring and Logging Practice Question
This DOP-C02 practice question tests your understanding of monitoring and logging. 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. 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 is running a production application on Amazon ECS with AWS Fargate. The application has unpredictable traffic patterns and occasionally experiences increased latency. The DevOps team needs to configure scaling based on a custom metric that tracks the number of active user sessions in real time. Which solution will allow the team to scale the ECS service based on this custom metric?
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
Publish the custom metric to Amazon CloudWatch, then create a target tracking scaling policy in Application Auto Scaling for the ECS service.
Option C is correct. To scale an ECS service based on a custom metric like active user sessions, you can publish the metric to Amazon CloudWatch and then create a target tracking scaling policy in Application Auto Scaling for the ECS service. Application Auto Scaling uses the CloudWatch metric to automatically adjust the desired count. Option A is incorrect because AWS Auto Scaling is for EC2 Auto Scaling, not for ECS services; Application Auto Scaling is the correct service. Option B is incorrect because manual adjustment based on a dashboard does not provide automated scaling. Option D is incorrect because while a Lambda function could be used to update the desired count, it introduces unnecessary complexity and is not the recommended approach; using Application Auto Scaling with CloudWatch is the standard solution.
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.
- ✗
Use AWS Auto Scaling to scale the ECS service based on the custom metric.
Why it's wrong here
AWS Auto Scaling is not directly used for ECS Service Auto Scaling; Application Auto Scaling is used.
- ✗
Create a CloudWatch dashboard to visualize the metric and manually adjust the service count.
Why it's wrong here
Manual intervention is not automated scaling.
- ✓
Publish the custom metric to Amazon CloudWatch, then create a target tracking scaling policy in Application Auto Scaling for the ECS service.
Why this is correct
This is the recommended approach for scaling ECS services using custom metrics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use an AWS Lambda function to directly update the desired count of the ECS service based on the metric.
Why it's wrong here
Lambda can be used but it is not a best practice; CloudWatch and Application Auto Scaling provide a native solution.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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.
Quick reference
Cloud Service Model Comparison
| Model | You Manage | Provider Manages | Examples |
|---|---|---|---|
| IaaS | OS, runtime, apps, data | Hardware, hypervisor, networking | EC2, Azure VMs, GCP Compute Engine |
| PaaS | Apps and data | OS, runtime, middleware, hardware | Elastic Beanstalk, Azure App Service |
| SaaS | Data and settings only | Everything else | Microsoft 365, Salesforce, Workday |
| FaaS / Serverless | Function code only | Infra, scaling, runtime | Lambda, Azure Functions, Cloud Run |
| CaaS | Containers and apps | Kubernetes, OS, hardware | EKS, AKS, GKE |
What to study next
Got this wrong? Here's your next step.
Identify which DOP-C02 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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FAQ
Questions learners often ask
What does this DOP-C02 question test?
Monitoring and Logging — This question tests Monitoring and Logging — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Publish the custom metric to Amazon CloudWatch, then create a target tracking scaling policy in Application Auto Scaling for the ECS service. — Option C is correct. To scale an ECS service based on a custom metric like active user sessions, you can publish the metric to Amazon CloudWatch and then create a target tracking scaling policy in Application Auto Scaling for the ECS service. Application Auto Scaling uses the CloudWatch metric to automatically adjust the desired count. Option A is incorrect because AWS Auto Scaling is for EC2 Auto Scaling, not for ECS services; Application Auto Scaling is the correct service. Option B is incorrect because manual adjustment based on a dashboard does not provide automated scaling. Option D is incorrect because while a Lambda function could be used to update the desired count, it introduces unnecessary complexity and is not the recommended approach; using Application Auto Scaling with CloudWatch is the standard solution.
What should I do if I get this DOP-C02 question wrong?
Identify which DOP-C02 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 20, 2026
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