SAP-C02 Continuous Improvement for Existing Solutions Practice Question
A company runs a batch processing application on AWS. The application reads input files from an S3 bucket, processes them on EC2 instances, and writes results to another S3 bucket. The processing job runs once a day and takes approximately 3 hours. The company wants to reduce costs and operational overhead. The Solutions Architect suggests using AWS Lambda for processing, but the processing time per file can exceed the Lambda maximum execution time of 15 minutes. The architect also considers using AWS Batch. The company wants to minimize the need for infrastructure management. Which solution should the Solutions Architect recommend?
⚠ Common exam trap
SAP-C02 often tests the Lambda 15-minute limit versus long-running batch workloads, and candidates may pick Lambda with more memory or ECS/Fargate without recognizing that AWS Batch is the managed service designed for queue-based, long-running, cost-optimized batch processing.
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
✓
Use AWS Batch with a managed compute environment that uses Spot Instances and a job queue.
AWS Batch with a managed compute environment using Spot Instances and a job queue is the best fit: it handles job scheduling, provisioning, and scaling automatically, eliminating infrastructure management, while Spot Instances reduce cost for the daily 3-hour batch job. It supports long-running jobs that exceed Lambda's 15-minute limit and is purpose-built for batch workloads. This satisfies both the cost-reduction and operational-overhead-minimization 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.
- ✗
Provision a fleet of EC2 instances and use Auto Scaling to manage the processing.
Why it's wrong here
Auto Scaling manages EC2 capacity but leaves patching, AMI updates and scaling policies to the company, so it does not meet the minimise-infrastructure-management requirement. It is tempting because Auto Scaling suits steady, long-running fleets where you control the instances; AWS Batch instead provisions managed compute and queues jobs without that overhead.
- ✗
Use AWS Lambda with a larger memory allocation to increase CPU and reduce processing time.
Why it's wrong here
Lambda's 15-minute execution limit is a hard cap, so larger memory cannot extend it; memory only scales CPU proportionally and the file may still exceed the limit. Lambda suits short, event-driven tasks, whereas AWS Batch with Fargate removes infrastructure management for longer jobs.
- ✓
Use AWS Batch with a managed compute environment that uses Spot Instances and a job queue.
Why this is correct
AWS Batch with a managed compute environment removes server infrastructure management, satisfying the minimal-overhead constraint, while Spot Instances cut cost for the 3-hour daily batch. It also lifts the 15-minute Lambda execution ceiling that blocked per-file processing.
- ✗
Use Amazon ECS with Fargate launch type and run the processing as a task.
Why it's wrong here
Fargate runs containers without server management, yet ECS gives no native job queue, dependency handling or array scheduling, so the batch workflow must be built manually. It is tempting because Fargate suits long-running containerised services; AWS Batch is purpose-built for queued batch jobs with managed compute environments.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
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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.