- A
Amazon ECS with the EC2 launch type
Why wrong: This option requires you to provision and manage the underlying EC2 instances that host the containers. You pay for the EC2 instances even when they are not running containers, and you must handle patching and scaling of the cluster.
- B
AWS Fargate
Fargate is a serverless compute engine for containers. You define the tasks and containers, and Fargate manages the infrastructure. You pay only for the vCPU and memory used by each running container, with no idle costs.
- C
Amazon EKS with managed node groups
Why wrong: Managed node groups reduce the operational overhead of managing the EC2 instances used as Kubernetes worker nodes, but you still pay for the EC2 instances. The underlying instances are managed for you, but you are billed for the instance hours, not just container resource usage.
- D
AWS Lambda
Why wrong: Lambda is a serverless compute service for running code in response to events, but it is designed for individual functions, not for running containers natively. While you can package code as container images for Lambda, it is not intended for deploying full microservices as containers, and the pricing model is based on execution time and requests, not on vCPU and memory for containerized applications.
CLF-C02 Cloud Technology and Services Practice Question
This CLF-C02 practice question tests your understanding of cloud technology and services. 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 development team is migrating a monolithic application to a microservices architecture. Each microservice will run in a separate container. The team wants to deploy and scale these containers without managing any underlying servers or clusters. The team also wants to pay only for the vCPU and memory resources consumed by each container, not for any idle capacity. Which AWS compute service should the team 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
AWS Fargate
AWS Fargate is the correct choice because it is a serverless compute engine for containers that allows you to run containers without managing any underlying servers or clusters. With Fargate, you pay only for the vCPU and memory resources consumed by each container, not for any idle capacity, which directly matches the team's requirements.
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.
- ✗
Amazon ECS with the EC2 launch type
Why it's wrong here
This option requires you to provision and manage the underlying EC2 instances that host the containers. You pay for the EC2 instances even when they are not running containers, and you must handle patching and scaling of the cluster.
- ✓
AWS Fargate
Why this is correct
Fargate is a serverless compute engine for containers. You define the tasks and containers, and Fargate manages the infrastructure. You pay only for the vCPU and memory used by each running container, with no idle costs.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Amazon EKS with managed node groups
Why it's wrong here
Managed node groups reduce the operational overhead of managing the EC2 instances used as Kubernetes worker nodes, but you still pay for the EC2 instances. The underlying instances are managed for you, but you are billed for the instance hours, not just container resource usage.
- ✗
AWS Lambda
Why it's wrong here
Lambda is a serverless compute service for running code in response to events, but it is designed for individual functions, not for running containers natively. While you can package code as container images for Lambda, it is not intended for deploying full microservices as containers, and the pricing model is based on execution time and requests, not on vCPU and memory for containerized applications.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the EC2 launch type with Fargate, thinking that ECS itself is serverless, but the EC2 launch type still requires server management and pays for idle capacity, while Fargate is the truly serverless option.
Detailed technical explanation
How to think about this question
AWS Fargate abstracts the underlying infrastructure by using a shared kernel and a lightweight VM (microVM) per task, which provides strong isolation without the overhead of managing EC2 instances. Under the hood, Fargate tasks are scheduled on a fleet of EC2 instances managed by AWS, but you never see or manage them; billing is based on the vCPU and memory requested per task, measured per second. In a real-world scenario, if a microservice experiences variable traffic, Fargate can scale tasks up and down automatically, and you only pay for the resources consumed during execution, eliminating the cost of idle EC2 instances.
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 CLF-C02 question test?
Cloud Technology and Services — This question tests Cloud Technology and Services — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AWS Fargate — AWS Fargate is the correct choice because it is a serverless compute engine for containers that allows you to run containers without managing any underlying servers or clusters. With Fargate, you pay only for the vCPU and memory resources consumed by each container, not for any idle capacity, which directly matches the team's requirements.
What should I do if I get this CLF-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
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Last reviewed: Jun 11, 2026
This CLF-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 CLF-C02 exam.
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