SAP-C02 Practice Question: Accelerate Workload Migration and Modernization
A media company is migrating a large on-premises video rendering workload to AWS. The workload runs on 100 physical servers and is highly parallelizable. The company wants to minimize infrastructure management and only pay for the compute capacity used. They also need to handle sudden spikes in demand. Which AWS service should they use?
⚠ Common exam trap
The trap here is assuming that any serverless compute service like Lambda or Fargate is suitable for batch workloads; AWS Batch is purpose-built for batch processing with job queues and dependencies.
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 designed for batch computing workloads, providing managed job scheduling and dynamic scaling. It supports both EC2 and Fargate compute environments and can leverage Spot Instances for cost savings. This allows the media company to run parallel rendering jobs without managing infrastructure, while paying only for the resources used, and it scales automatically to handle spikes in demand.
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 compute service, but it has a maximum execution timeout of 15 minutes and limited temporary storage. Video rendering tasks often exceed these limits, especially for high-resolution content. Lambda is not suitable for long-running, compute-intensive workloads. While it scales automatically, the constraints make it a poor fit for this scenario, and it would require significant re-architecture to split rendering into smaller chunks.
- ✓
AWS Batch
Why this is correct
AWS Batch is a fully managed batch computing service that dynamically provisions compute resources based on job volume and requirements. It handles job scheduling, dependency management, and scaling, allowing the company to focus on rendering jobs. It integrates with Spot Instances for cost savings and can scale to handle spikes. This minimizes infrastructure management and aligns with pay-for-use pricing.
- ✗
Amazon ECS with Fargate
Why it's wrong here
Amazon ECS with Fargate is a serverless container service, but it is not optimized for batch workloads. While it reduces infrastructure management, it lacks native job scheduling and queueing. You would need to build a custom system using SQS and other services. For a highly parallelizable batch workload, AWS Batch provides a more integrated and efficient solution, with built-in job definitions, queues, and compute environment management.
- ✗
Amazon EC2 with Spot Instances
Why it's wrong here
Amazon EC2 Spot Instances offer significant cost savings but require you to manage the instances, including provisioning, patching, and scaling. They can be interrupted with a two-minute warning, which may be problematic for rendering tasks that cannot checkpoint. While cost-effective, they do not minimize infrastructure management as effectively as a serverless compute service, and handling sudden spikes requires additional auto scaling configuration.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
This SAP-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 SAP-C02 exam.