CLF-C02 Cloud Technology and Services Practice Question
A company needs to run a data processing job that typically takes 2 hours to complete. The job is stateless and can be parallelized across multiple workers. The company wants to minimize operational overhead and only pay for the compute time consumed. The job runs only once a month. Which AWS compute service should the company use?
⚠ Common exam trap
Many exam-takers choose AWS Lambda for any serverless or 'pay-per-use' scenario, forgetting its hard 15-minute timeout limit, or they pick Fargate thinking it handles batch jobs natively, when in fact AWS Batch is the dedicated service for batch computing with built-in scheduling and scaling.
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 Batch
AWS Batch is the correct choice because it is designed for running batch computing workloads that are stateless, parallelizable, and can run on a schedule. It automatically provisions and manages the underlying compute resources (EC2 or Fargate), scales to the required number of workers, and only charges for the compute time consumed. The 2-hour, once-a-month job fits perfectly within AWS Batch's capabilities, and it minimizes operational overhead by handling job queuing, retries, and dependency management.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
AWS Lambda
Why it's wrong here
AWS Lambda is a serverless, event-driven compute service that executes functions in response to triggers, but it enforces a hard maximum execution timeout of 15 minutes (900 seconds) per invocation. A data processing job that typically takes 2 hours cannot fit within this limit, so Lambda is architecturally incapable of running the workload without significant refactoring into many short-lived, state-coordinated steps (e.g., using Step Functions), which changes the solution's design and adds orchestration complexity. Even with fan-out or chunking, the job itself remains a long-running batch process, not a set of small event handlers, making Lambda a poor fit for the stated requirements.
- ✗
Amazon EC2 Spot Instances
Why it's wrong here
While Spot Instances can be cost-effective, using EC2 directly to run a batch job requires the company to manage instance provisioning, Auto Scaling, monitoring, and job scheduling. This results in significantly higher operational overhead compared to using a fully managed service like AWS Batch.
- ✗
AWS Fargate
Why it's wrong here
AWS Fargate is a serverless compute engine for containers that removes the need to manage underlying servers. However, it does not include built-in job scheduling, queue management, or automatic scaling for batch jobs. To run a batch workload on Fargate, the company would need to set up an orchestrator (e.g., Amazon ECS with custom scheduling) and handle job dependencies, increasing complexity vs. AWS Batch.
When this WOULD be correct
A company needs to run a containerized web application that scales based on traffic, with no need for job scheduling or parallel batch processing. The application runs continuously and the company wants to avoid managing servers or clusters. AWS Fargate would be the correct choice for running containers without managing underlying infrastructure.
- ✓
AWS Batch
Why this is correct
AWS Batch is purpose-built for batch computing. It automatically provisions the required compute resources (including Spot Instances) based on job requirements, manages job queues, retries, and dependencies. The company pays only for the underlying compute resources consumed. This combination of minimal operational overhead and pay-per-use pricing makes AWS Batch the best fit for this scenario.
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 BatchCorrect answer▾
Why this is correct
AWS Batch is purpose-built for batch computing. It automatically provisions the required compute resources (including Spot Instances) based on job requirements, manages job queues, retries, and dependencies. The company pays only for the underlying compute resources consumed. This combination of minimal operational overhead and pay-per-use pricing makes AWS Batch the best fit for this scenario.
✗AWS FargateWrong answer — click to see why▾
Why this is wrong here
AWS Fargate is a serverless compute engine for containers, but it lacks native job scheduling and parallelization features for batch processing. The job runs only once a month and requires minimal operational overhead, but Fargate would require manual setup of container orchestration and does not automatically manage job queues or retries like AWS Batch.
★ When this WOULD be the correct answer
A company needs to run a containerized web application that scales based on traffic, with no need for job scheduling or parallel batch processing. The application runs continuously and the company wants to avoid managing servers or clusters. AWS Fargate would be the correct choice for running containers without managing underlying infrastructure.
Why candidates choose this
Candidates may choose Fargate because it is serverless and can run containers, assuming it handles batch jobs similarly to Lambda, but they overlook that AWS Batch is specifically designed for batch computing with job scheduling and parallel execution capabilities.
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?”
Go deeper
Related to this question
About these practice questions
This CLF-C02 question is part of Courseiva's 988-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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.