- A
Use Amazon EC2 Auto Scaling to add more Fargate tasks.
Why wrong: EC2 Auto Scaling manages EC2 instances, not Fargate tasks; ECS Service Auto Scaling is needed.
- B
Configure Application Auto Scaling with a target tracking scaling policy based on average CPU utilization.
Application Auto Scaling with target tracking is the standard method to automatically scale ECS services based on a metric like CPU.
- C
Use AWS Auto Scaling Plans with predictive scaling.
Why wrong: AWS Auto Scaling Plans is for multi-resource scaling, but for ECS services, Application Auto Scaling with target tracking is more appropriate.
- D
Manually adjust the desired count of tasks in the ECS service based on traffic analysis.
Why wrong: Manual scaling is not automated and does not meet the requirement for automatic scaling.
Quick Answer
The correct choice is to configure Application Auto Scaling with a target tracking scaling policy based on average CPU utilization. This solution works because Amazon ECS with the Fargate launch type relies on Application Auto Scaling to dynamically adjust the desired task count, and a target tracking policy maintains a specified metric—such as 70% average CPU—by automatically adding or removing tasks in response to demand. On the AWS Certified Solutions Architect Professional SAP-C02 exam, this scenario tests your understanding of how to implement auto scaling for ECS Fargate services under variable traffic patterns, often contrasting it with scheduled scaling or step scaling policies. A common trap is selecting a simple CloudWatch alarm-based step scaling policy, which requires manual threshold tuning and can react too aggressively. Remember the memory tip: “Track the target, not the steps”—target tracking policies are the simplest and most effective way to auto scale ECS Fargate services based on steady-state utilization metrics.
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 microservices application on AWS. Each microservice will be deployed as a containerized application using Amazon ECS with Fargate launch type. The company expects variable traffic patterns and needs to ensure that the application can scale automatically based on demand. Which scaling solution should be used?
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 Application Auto Scaling with a target tracking scaling policy based on average CPU utilization.
Amazon ECS with Fargate uses Application Auto Scaling to automatically adjust the desired count of tasks based on demand. A target tracking scaling policy based on average CPU utilization is the correct approach because it allows you to define a target value (e.g., 70% CPU) and Application Auto Scaling will add or remove tasks to maintain that target, matching the variable traffic patterns described.
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 Amazon EC2 Auto Scaling to add more Fargate tasks.
Why it's wrong here
EC2 Auto Scaling manages EC2 instances, not Fargate tasks; ECS Service Auto Scaling is needed.
- ✓
Configure Application Auto Scaling with a target tracking scaling policy based on average CPU utilization.
Why this is correct
Application Auto Scaling with target tracking is the standard method to automatically scale ECS services based on a metric like CPU.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use AWS Auto Scaling Plans with predictive scaling.
Why it's wrong here
AWS Auto Scaling Plans is for multi-resource scaling, but for ECS services, Application Auto Scaling with target tracking is more appropriate.
- ✗
Manually adjust the desired count of tasks in the ECS service based on traffic analysis.
Why it's wrong here
Manual scaling is not automated and does not meet the requirement for automatic scaling.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is confusing EC2 Auto Scaling (which manages instances) with Application Auto Scaling (which manages ECS tasks), leading candidates to choose Option A despite Fargate being serverless and not requiring EC2 instance management.
Detailed technical explanation
How to think about this question
Application Auto Scaling for ECS services uses the AWS Application Auto Scaling API, which integrates with CloudWatch alarms to trigger scaling actions. For target tracking policies, you specify a predefined metric (e.g., ECS Service Average CPUUtilization) and a target value; the scaling algorithm uses a proportional-integral-derivative (PID) controller to adjust the task count smoothly, avoiding oscillations. In a real-world scenario, if traffic spikes suddenly, the policy will scale out tasks quickly, but you must also configure a cooldown period to prevent thrashing.
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.
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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 Application Auto Scaling with a target tracking scaling policy based on average CPU utilization. — Amazon ECS with Fargate uses Application Auto Scaling to automatically adjust the desired count of tasks based on demand. A target tracking scaling policy based on average CPU utilization is the correct approach because it allows you to define a target value (e.g., 70% CPU) and Application Auto Scaling will add or remove tasks to maintain that target, matching the variable traffic patterns described.
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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on SAP-C02
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is designing a multi-tier web application on AWS. They want to ensure that the web tier can scale automatically based on CPU utilization. Which AWS service should they use?
medium- A.Amazon CloudFront
- B.Amazon Route 53
- ✓ C.Auto Scaling groups
- D.Elastic Load Balancing
Why C: Option A is correct because Auto Scaling groups can automatically adjust capacity based on CloudWatch alarms. Option B is wrong because Elastic Load Balancing distributes traffic but does not scale. Option C is wrong because CloudFront is a CDN. Option D is wrong because Route 53 is DNS.
Variation 2. A company is designing a multi-tier web application that must be fault-tolerant and scalable. The application uses an Application Load Balancer (ALB) to distribute traffic to EC2 instances in an Auto Scaling group. The instances run a web server and a backend application. Which TWO steps should be taken to ensure the application can scale without data loss?
medium- A.Use instance store volumes for temporary data.
- ✓ B.Store session state in an external data store such as ElastiCache.
- ✓ C.Implement lifecycle hooks to gracefully handle instance termination.
- D.Use a custom CloudWatch metric to scale based on CPU utilization.
- E.Use a fixed number of EC2 instances instead of Auto Scaling.
Why B: Option B is correct because storing session state in an external data store like ElastiCache decouples session data from individual EC2 instances. This ensures that if an instance is terminated or replaced during scaling events, the session data persists and can be served by any other instance in the Auto Scaling group, preventing data loss and maintaining user experience.
Last reviewed: Jun 24, 2026
This SAP-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 SAP-C02 exam.
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