MLS-C01 Data Engineering Practice Question
A company is using Amazon DynamoDB as a source for a machine learning pipeline. The data is exported nightly to Amazon S3 using DynamoDB Streams and an AWS Glue job. The Glue job reads the stream records, transforms them, and writes to S3 in Parquet format. The team notices that the Glue job is taking too long and consuming high DynamoDB read capacity. Which THREE actions would reduce the load on DynamoDB and improve performance? (Choose THREE.)
⚠ Common exam trap
Watch out — candidates often assume increasing DynamoDB capacity (RCUs or WCUs) is the solution to performance issues, but the exam tests understanding that native export features and architectural changes (like using Lambda or S3 snapshots) can eliminate the root cause of high read consumption without scaling capacity.
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 DynamoDB export to S3 (incremental) feature instead of Glue
DynamoDB's native export to S3 (incremental) feature directly exports data to S3 without consuming read capacity units (RCUs) or requiring a separate compute service like AWS Glue. This eliminates the bottleneck of Glue reading from DynamoDB Streams, which consumes RCUs and adds latency, thereby reducing load on DynamoDB and improving overall performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use Amazon DynamoDB export to S3 (incremental) feature instead of Glue
Why this is correct
The export feature does not consume read capacity and can be automated.
- ✗
Increase the DynamoDB write capacity units to handle the stream writes
Why it's wrong here
Write capacity is for writes, not relevant to Glue's reads.
- ✓
Use DynamoDB Streams with AWS Lambda to write data directly to S3 in near-real-time, bypassing Glue
Why this is correct
Lambda can write to S3 without consuming DynamoDB read capacity repeatedly.
- ✗
Increase the DynamoDB read capacity units to handle Glue's workload
Why it's wrong here
Increasing read capacity increases cost and load, not reduces.
- ✓
Configure Glue to read from a S3 snapshot exported earlier instead of directly from DynamoDB
Why this is correct
Reading from S3 reduces the load on DynamoDB.
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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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.