- 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.
AWS Fargate: Serverless Compute for Containers with Pay-as-You-Go Pricing
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.
When this WOULD be correct
A team wants to deploy containers on AWS but needs full control over the underlying EC2 instances for compliance or custom configuration, and is willing to manage the cluster and pay for idle capacity.
- ✓
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.
When this WOULD be correct
This option would be correct if the team needed to run Kubernetes-based containers and was willing to manage the worker nodes (even if the control plane is managed), or if they required specific Kubernetes features not available on Fargate, and they accepted paying for idle EC2 capacity.
- ✗
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.
When this WOULD be correct
A team needs to run a small, event-driven data processing task that executes in under 15 minutes, such as resizing images uploaded to S3. They want to pay only for compute time used and avoid managing servers. In that case, AWS Lambda is the correct choice.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The CLF-C02 exam frequently reuses these exact scenarios with slightly different constraints.
✓AWS FargateCorrect answer▾
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.
✗Amazon ECS with the EC2 launch typeWrong answer — click to see why▾
Why this is wrong here
Amazon ECS with the EC2 launch type requires managing underlying EC2 instances, which violates the requirement to not manage any underlying servers or clusters. Additionally, you pay for the EC2 instances even when idle, not just for the vCPU and memory consumed by each container.
★ When this WOULD be the correct answer
A team wants to deploy containers on AWS but needs full control over the underlying EC2 instances for compliance or custom configuration, and is willing to manage the cluster and pay for idle capacity.
Why candidates choose this
Candidates may confuse ECS with Fargate, thinking ECS always abstracts servers, but the EC2 launch type does not; they overlook the 'without managing servers' constraint.
✗Amazon EKS with managed node groupsWrong answer — click to see why▾
Why this is wrong here
Amazon EKS with managed node groups still requires managing EC2 instances (the node groups), which violates the requirement to not manage any underlying servers or clusters. Additionally, you pay for the EC2 instances even when idle, not just for vCPU and memory consumed per container.
★ When this WOULD be the correct answer
This option would be correct if the team needed to run Kubernetes-based containers and was willing to manage the worker nodes (even if the control plane is managed), or if they required specific Kubernetes features not available on Fargate, and they accepted paying for idle EC2 capacity.
Why candidates choose this
Candidates may think 'managed node groups' means fully serverless, but it only manages the control plane; the worker nodes are still EC2 instances that incur costs and require management.
✗AWS LambdaWrong answer — click to see why▾
Why this is wrong here
AWS Lambda is event-driven and designed for short-running, stateless functions, not for long-running containerized microservices. It does not support running arbitrary Docker containers directly, and its pricing is based on invocations and duration, not vCPU/memory per container.
★ When this WOULD be the correct answer
A team needs to run a small, event-driven data processing task that executes in under 15 minutes, such as resizing images uploaded to S3. They want to pay only for compute time used and avoid managing servers. In that case, AWS Lambda is the correct choice.
Why candidates choose this
Candidates may think Lambda's serverless model and pay-per-use pricing align with the requirement to avoid managing servers and pay only for consumed resources, overlooking that Lambda does not support containerized microservices with persistent workloads.
Analysis generated from the official CLF-C02blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
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.
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
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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
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
1 more ways this is tested on CLF-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 refactoring its legacy application into a microservices architecture using Docker containers. The operations team wants to deploy and manage these containers on AWS without the need to provision, patch, or manage the underlying servers. The solution must automatically scale containers based on demand and integrate with services like Application Load Balancer and Amazon RDS. Which AWS compute service should the company use?
medium- A.Amazon ECS with Amazon EC2 launch type
- ✓ B.Amazon ECS with AWS Fargate launch type
- C.AWS Lambda
- D.Amazon EC2 instances with Docker installed
Why B: Amazon ECS with AWS Fargate launch type is the correct choice because it is a serverless compute engine for containers that eliminates the need to provision, patch, or manage underlying servers. Fargate automatically scales containers based on demand and integrates natively with services like Application Load Balancer and Amazon RDS, meeting all the stated requirements.
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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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