- A
Configure an ECS Service Auto Scaling policy with a target tracking scaling policy based on a custom CloudWatch metric.
ECS Service Auto Scaling supports target tracking for custom metrics.
- B
Configure Amazon DynamoDB auto scaling to adjust the read capacity based on the request count.
Why wrong: DynamoDB auto scaling is for database throughput, not ECS tasks.
- C
Use Application Auto Scaling to register the ECS service and create a step scaling policy.
Why wrong: While Application Auto Scaling can be used, the more direct solution is ECS Service Auto Scaling with target tracking.
- D
Use the AWS Auto Scaling console to create a scaling plan that includes the ECS service.
Why wrong: The AWS Auto Scaling console is a unified interface, but the underlying mechanism is still ECS Service Auto Scaling.
SAP-C02 Design for New Solutions Practice Question
This SAP-C02 practice question tests your understanding of design for new solutions. 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 designing a new web application that will be deployed on Amazon ECS with Fargate. The application must scale based on the number of requests per container. The company wants to use a service that can automatically adjust the number of tasks based on a custom metric. Which solution should the company use?
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
Configure an ECS Service Auto Scaling policy with a target tracking scaling policy based on a custom CloudWatch metric.
Option A is correct because ECS Service Auto Scaling with a target tracking scaling policy can use a custom CloudWatch metric (e.g., requests per container) to automatically adjust the number of Fargate tasks. This approach directly matches the requirement to scale based on a custom metric, as target tracking maintains the metric at a specified target value by adding or removing tasks.
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 an ECS Service Auto Scaling policy with a target tracking scaling policy based on a custom CloudWatch metric.
Why this is correct
ECS Service Auto Scaling supports target tracking for custom metrics.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Configure Amazon DynamoDB auto scaling to adjust the read capacity based on the request count.
Why it's wrong here
DynamoDB auto scaling is for database throughput, not ECS tasks.
- ✗
Use Application Auto Scaling to register the ECS service and create a step scaling policy.
Why it's wrong here
While Application Auto Scaling can be used, the more direct solution is ECS Service Auto Scaling with target tracking.
- ✗
Use the AWS Auto Scaling console to create a scaling plan that includes the ECS service.
Why it's wrong here
The AWS Auto Scaling console is a unified interface, but the underlying mechanism is still ECS Service Auto Scaling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates may confuse step scaling with target tracking, or incorrectly assume that a scaling plan from the AWS Auto Scaling console is required for ECS services, when in fact ECS Service Auto Scaling with target tracking is the direct and recommended solution for custom metrics.
Detailed technical explanation
How to think about this question
Under the hood, ECS Service Auto Scaling uses Application Auto Scaling APIs to adjust the desired count of tasks based on CloudWatch alarms. Target tracking scaling policies automatically create and manage CloudWatch alarms to keep the custom metric (e.g., requests per container) close to the target value, smoothing out fluctuations without manual intervention. In a real-world scenario, this is ideal for web apps with variable traffic, as it avoids over-provisioning or under-provisioning tasks.
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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Design for New Solutions — study guide chapter
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FAQ
Questions learners often ask
What does this SAP-C02 question test?
Design for New Solutions — This question tests Design for New Solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Configure an ECS Service Auto Scaling policy with a target tracking scaling policy based on a custom CloudWatch metric. — Option A is correct because ECS Service Auto Scaling with a target tracking scaling policy can use a custom CloudWatch metric (e.g., requests per container) to automatically adjust the number of Fargate tasks. This approach directly matches the requirement to scale based on a custom metric, as target tracking maintains the metric at a specified target value by adding or removing tasks.
What should I do if I get this SAP-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
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