- A
Configure DynamoDB auto scaling to adjust read capacity based on queue depth.
Why wrong: DynamoDB auto scaling is unrelated to ECS task scaling.
- B
Use Amazon ECS Service Auto Scaling with a target tracking scaling policy based on the SQS queue backlog per task.
This allows dynamic scaling based on queue depth.
- C
Configure AWS Lambda with reserved concurrency and trigger it from the SQS queue.
Why wrong: Lambda reserved concurrency does not scale ECS tasks.
- D
Use Application Auto Scaling with a scheduled scaling policy to increase the number of tasks during peak hours.
Why wrong: Scheduled scaling does not respond to real-time queue depth changes.
Question 1,053 of 1,616
DVA-C02 Deployment Practice Question
This DVA-C02 practice question tests your understanding of deployment. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 deploying a microservices application on Amazon ECS using the Fargate launch type. The application includes a service that must process messages from an Amazon SQS queue. The developer wants to ensure that the service scales based on the number of messages in the queue. Which scaling solution should the developer implement?
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 Amazon ECS Service Auto Scaling with a target tracking scaling policy based on the SQS queue backlog per task.
Option B is correct because Amazon ECS Service Auto Scaling with a target tracking scaling policy based on the SQS queue backlog per task (calculated as ApproximateNumberOfMessages divided by the number of running tasks) directly correlates the number of ECS tasks to the queue depth. This ensures the service scales up when messages accumulate and scales down when the backlog clears, using a predefined or custom metric that reflects the workload.
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.
- ✗
Configure DynamoDB auto scaling to adjust read capacity based on queue depth.
Why it's wrong here
DynamoDB auto scaling is unrelated to ECS task scaling.
- ✓
Use Amazon ECS Service Auto Scaling with a target tracking scaling policy based on the SQS queue backlog per task.
Why this is correct
This allows dynamic scaling based on queue depth.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure AWS Lambda with reserved concurrency and trigger it from the SQS queue.
Why it's wrong here
Lambda reserved concurrency does not scale ECS tasks.
- ✗
Use Application Auto Scaling with a scheduled scaling policy to increase the number of tasks during peak hours.
Why it's wrong here
Scheduled scaling does not respond to real-time queue depth changes.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse service auto scaling with scheduled scaling or assume Lambda is the only serverless option, missing that ECS with Fargate can scale based on SQS backlog using a target tracking policy.
Detailed technical explanation
How to think about this question
The target tracking policy uses the `ALBRequestCountPerTarget` or a custom `SQSQueueBacklogPerTask` metric, which is calculated as `ApproximateNumberOfMessages` / `RunningTaskCount`. The scaling cooldown period (default 300 seconds) prevents rapid fluctuations, and the policy automatically creates CloudWatch alarms to maintain the target value (e.g., 1000 messages per task). This approach is ideal for variable workloads where queue depth is the primary driver of demand.
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
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this DVA-C02 question test?
Deployment — This question tests Deployment — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use Amazon ECS Service Auto Scaling with a target tracking scaling policy based on the SQS queue backlog per task. — Option B is correct because Amazon ECS Service Auto Scaling with a target tracking scaling policy based on the SQS queue backlog per task (calculated as ApproximateNumberOfMessages divided by the number of running tasks) directly correlates the number of ECS tasks to the queue depth. This ensures the service scales up when messages accumulate and scales down when the backlog clears, using a predefined or custom metric that reflects the workload.
What should I do if I get this DVA-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: Jul 4, 2026
This DVA-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 DVA-C02 exam.
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