MLS-C01 Data Engineering Practice Question
A company uses AWS Lambda to process events from Amazon S3. The Lambda function transforms the data and writes results to another S3 bucket. Recently, the function has been failing due to timeout errors when processing large files. Which solution should the data engineer implement?
⚠ Common exam trap
Candidates often assume increasing timeout or memory (Option A) is the universal fix for Lambda failures, but the real issue is the synchronous invocation model from S3 events, which S3 Batch Operations solves by decoupling the 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 S3 Batch Operations with a Lambda function to process objects
S3 Batch Operations is designed to handle large-scale object processing by invoking a Lambda function asynchronously for each object, bypassing the synchronous invocation limits of S3 event notifications. This allows processing of large files without hitting Lambda's 15-minute timeout or memory constraints, as each object is processed independently and the operation can scale to billions of objects.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the Lambda function memory and timeout limit
Why it's wrong here
Lambda has a maximum timeout of 15 minutes; large files may still exceed.
- ✗
Increase the Lambda timeout to 15 minutes
Why it's wrong here
May not be enough for very large files and not a scalable solution.
- ✓
Use S3 Batch Operations with a Lambda function to process objects
Why this is correct
Batch Operations can invoke Lambda for each object, handling large volumes.
- ✗
Use Amazon SQS to queue the events and process them in batches
Why it's wrong here
SQS does not address the processing of large files within Lambda.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This MLS-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 MLS-C01 exam.