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Cloud Technology and ServicesmediumMultiple ChoiceObjective-mapped

CLF-C02 Cloud Technology and Services Practice Question

A company runs a batch processing application in Docker containers. The application runs for several hours at a time and requires significant CPU and memory resources. The company wants to run these containers on AWS without provisioning or managing any underlying EC2 instances or cluster capacity. They need a service that automatically scales based on demand and charges only for the resources consumed by the containers. Which AWS service should the company use?

⚠ Common exam trap

Candidates often confuse the EC2 launch type (which still requires instance management) with Fargate's serverless model, or they assume managed node groups in EKS eliminate all infrastructure management, when in fact they still involve EC2 instances and cluster scaling decisions.

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 eliminates the need to provision or manage EC2 instances. It automatically scales based on demand and charges only for the CPU and memory resources consumed by the containers, which aligns perfectly with the requirement to run long-running batch processing without managing underlying infrastructure.

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 EC2 launch type

    Why it's wrong here

    Amazon ECS with the EC2 launch type is incorrect because it requires you to provision, configure, patch, and manage a cluster of EC2 instances that serve as the compute layer for your containers. You are responsible for capacity planning, Auto Scaling group configuration, OS patching, and instance health monitoring, which violates the requirement to avoid managing underlying servers. Although ECS orchestrates containers, the EC2 launch type shifts significant operational overhead to the customer, unlike a serverless option such as Fargate. This approach also incurs costs for idle EC2 instances, even when no batch jobs are running, further undermining efficiency.

    When this WOULD be correct

    A company needs to run Docker containers on AWS and requires full control over the underlying EC2 instances for compliance or custom configurations, and is willing to manage the cluster capacity.

  • Amazon EKS with managed node groups

    Why it's wrong here

    Amazon EKS with managed node groups still requires you to manage worker node groups, albeit with some automation from AWS. It does not provide a fully serverless experience as you are responsible for the node group's lifecycle.

    When this WOULD be correct

    When the company needs to run containerized applications on Kubernetes and is willing to manage EC2 instances (even if partially automated via managed node groups), or requires specific Kubernetes features not available on Fargate.

  • AWS Fargate

    Why this is correct

    AWS Fargate is the correct choice. It is a serverless compute engine for containers that runs on Amazon ECS or EKS. You define your containerized application and its resource requirements, and Fargate handles the underlying infrastructure, scaling, and billing per resource consumption.

  • AWS Lambda

    Why it's wrong here

    AWS Lambda is designed for short-running, event-driven functions with a maximum execution time of 15 minutes. It is not suitable for processing batch jobs that run for several hours. Additionally, Lambda's container image support is limited to images up to 10 GB, and it is not optimized for long-running, resource-intensive workloads.

    When this WOULD be correct

    A company needs to run short-duration, event-driven code (e.g., processing S3 uploads, responding to API calls) without provisioning servers, and the code runs in under 15 minutes with modest resource requirements.

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

AWS Fargate is the correct choice. It is a serverless compute engine for containers that runs on Amazon ECS or EKS. You define your containerized application and its resource requirements, and Fargate handles the underlying infrastructure, scaling, and billing per resource consumption.

Amazon ECS with EC2 launch typeWrong answer — click to see why

Why this is wrong here

Amazon ECS with EC2 launch type requires provisioning and managing EC2 instances, which contradicts the requirement to avoid managing underlying infrastructure.

★ When this WOULD be the correct answer

A company needs to run Docker containers on AWS and requires full control over the underlying EC2 instances for compliance or custom configurations, and is willing to manage the cluster capacity.

Why candidates choose this

Candidates may know ECS is for containers but overlook the distinction between EC2 and Fargate launch types, assuming ECS automatically implies serverless management.

Amazon EKS with managed node groupsWrong answer — click to see why

Why this is wrong here

Amazon EKS with managed node groups still requires provisioning and managing EC2 instances (the node groups), which violates the requirement to not manage underlying infrastructure.

★ When this WOULD be the correct answer

When the company needs to run containerized applications on Kubernetes and is willing to manage EC2 instances (even if partially automated via managed node groups), or requires specific Kubernetes features not available on Fargate.

Why candidates choose this

Candidates may confuse 'managed node groups' with fully serverless, not realizing that managed node groups still involve EC2 instances that must be provisioned and scaled.

AWS LambdaWrong answer — click to see why

Why this is wrong here

AWS Lambda has a maximum execution timeout of 15 minutes and limited CPU/memory (up to 10 GB memory), making it unsuitable for batch processing that runs for several hours and requires significant resources.

★ When this WOULD be the correct answer

A company needs to run short-duration, event-driven code (e.g., processing S3 uploads, responding to API calls) without provisioning servers, and the code runs in under 15 minutes with modest resource requirements.

Why candidates choose this

Candidates may confuse serverless compute with Fargate, overlooking Lambda's strict execution time and resource limits, and assume any containerized workload can run on Lambda.

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

ModelYou ManageProvider ManagesExamples
IaaSOS, runtime, apps, dataHardware, hypervisor, networkingEC2, Azure VMs, GCP Compute Engine
PaaSApps and dataOS, runtime, middleware, hardwareElastic Beanstalk, Azure App Service
SaaSData and settings onlyEverything elseMicrosoft 365, Salesforce, Workday
FaaS / ServerlessFunction code onlyInfra, scaling, runtimeLambda, Azure Functions, Cloud Run
CaaSContainers and appsKubernetes, OS, hardwareEKS, AKS, GKE

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Last reviewed: Jun 11, 2026

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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.