SAP-C02 Practice Question: Accelerate Workload Migration and Modernization
A company is migrating a large-scale batch processing system from on-premises to AWS. The system runs millions of short-lived jobs each day. The company wants to minimize operational overhead and cost. Which AWS compute service should the company 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 Batch
AWS Batch is specifically designed for batch computing workloads, handling millions of short-lived jobs efficiently by automatically provisioning compute resources and scaling based on job demand. It integrates with Spot Instances to reduce costs. Option A is wrong because EC2 with Spot Fleet requires manual management of instances and scaling, increasing operational overhead. Option B is wrong because ECS with Fargate is optimized for containerized applications, but AWS Batch provides more specialized features for batch job scheduling and cost optimization. Option C is wrong because Lambda has a maximum execution timeout of 15 minutes and is intended for short, event-driven functions, not suitable for batch processing.
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 EC2 with Spot Fleet
Why it's wrong here
Spot Fleet still requires the company to manage instance fleets, AMIs, and interruption handling, which does not minimise operational overhead for millions of short-lived jobs. Spot suits long-running, interruption-tolerant workloads such as continuous batch or CI runners, where capacity cost, not per-job orchestration, dominates.
- ✗
Amazon ECS with AWS Fargate
Why it's wrong here
Fargate still requires the team to build images, define task definitions, and manage cluster capacity and scheduling, adding operational overhead for millions of short-lived jobs. Fargate suits containerised services or long-running batch tasks where container portability matters more than per-job invocation cost.
- ✗
AWS Lambda
Why it's wrong here
Lambda is the correct answer here; it is not incorrect. It runs each short-lived job without servers, scaling automatically and charging per invocation, which minimises both operational overhead and cost for millions of daily jobs. No analysis of an incorrect option is required.
- ✓
AWS Batch
Why this is correct
AWS Batch dynamically provisions optimal compute (Spot or On-Demand) for millions of short-lived jobs, queues and schedules them automatically, and scales to zero between runs. This removes cluster management overhead and cuts cost versus continuously running servers.
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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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.