DEA-C01 Data Ingestion and Transformation Practice Question
A media company ingests video files from content partners into an Amazon S3 bucket. Each video file is 10-50 GB. Upon upload, an AWS Lambda function is triggered to extract metadata (e.g., resolution, duration) and store it in DynamoDB. The company now wants to also generate a thumbnail image for each video. The thumbnail generation is CPU-intensive and can take up to 5 minutes per video. The Lambda function has a maximum execution time of 15 minutes. The company has noticed that some thumbnail generation tasks are timing out. What should the data engineer do to reliably generate thumbnails for all videos?
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 to run a containerized thumbnail generation job triggered by S3 events
Use AWS Batch to run a containerized thumbnail generation job triggered by S3 events. AWS Batch is designed for long-running, compute-intensive workloads like video processing, and it can automatically scale resources based on the job queue. Option A (EC2 instance) requires manual management and scaling. Option B (Glue Python shell) is intended for ETL jobs, not CPU-intensive video processing. Option C (increasing Lambda timeout and memory) may still not be reliable for 5-minute thumbnail generation since Lambda has a maximum execution time of 15 minutes and is not optimized for heavy compute tasks; it could still time out or be cost-inefficient.
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 an EC2 instance to run a script that polls S3 for new videos and generates thumbnails
Why it's wrong here
Adds operational overhead and scaling issues.
- ✗
Use AWS Glue with a Python shell job to generate thumbnails
Why it's wrong here
Glue is for data transformation, not media processing.
- ✗
Increase the Lambda timeout to 15 minutes and allocate more memory
Why it's wrong here
Lambda is not ideal for CPU-intensive tasks; also, 15 min may still be insufficient.
- ✓
Use AWS Batch to run a containerized thumbnail generation job triggered by S3 events
Why this is correct
Batch is optimized for batch computing and can handle long-running jobs.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This DEA-C01 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 DEA-C01 exam.