CLF-C02 Cloud Technology and Services Practice Question
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?
⚠ Common exam trap
Test-takers frequently 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.
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.
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.
- ✗
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?”
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 |
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About these practice questions
Courseiva writes every CLF-C02 question from scratch — 988 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.