MLS-C01 Data Engineering Practice Question
A company is designing a data pipeline to process log files from multiple sources. The logs are written to Amazon S3 every hour. The data is then transformed using AWS Glue ETL jobs and loaded into Amazon Redshift for analysis. The company needs to ensure that the data is available for analysis within 30 minutes of being written to S3. Currently, the Glue job is triggered hourly, but the company wants to reduce the latency. Which solution should the company implement?
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 Amazon S3 event notifications to invoke an AWS Lambda function that starts the Glue job automatically
Configuring an S3 event notification to invoke AWS Lambda, which starts the Glue job, allows near-real-time processing within minutes. Option A is wrong because hourly triggers do not reduce latency. Option B is wrong because increasing the crawler frequency does not trigger ETL jobs. Option D is wrong because Redshift Spectrum does not transform data.
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 frequency of the Glue crawler to run every 5 minutes
Why it's wrong here
Crawlers update the Data Catalog, but do not trigger ETL jobs.
- ✗
Use Amazon Redshift Spectrum to query the data directly from S3 without transformation
Why it's wrong here
Spectrum queries data in place but does not perform transformations required by the pipeline.
- ✓
Use Amazon S3 event notifications to invoke an AWS Lambda function that starts the Glue job automatically
Why this is correct
S3 events trigger Lambda immediately, which starts the Glue job with low latency.
- ✗
Reduce the Glue job trigger frequency to every 15 minutes
Why it's wrong here
This still introduces up to 15 minutes of delay, not meeting the 30-minute requirement easily.
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.