MLS-C01 Data Engineering Practice Question
A data engineer is building a streaming pipeline using Amazon Kinesis Data Streams and AWS Lambda. The Lambda function processes records and writes results to Amazon S3. The engineer notices that the Lambda function is experiencing throttling and some records are being dropped. Which TWO actions should the engineer take to improve the reliability of the pipeline?
⚠ Common exam trap
Test-takers frequently confuse stream-level throttling with Lambda processing failures, leading them to choose a Dead Letter Queue (which handles processing failures) instead of addressing the root cause of insufficient throughput or concurrency.
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
✓
Increase the number of shards in the Kinesis data stream.
Increasing the number of shards in the Kinesis data stream directly increases the stream's throughput capacity. Each shard supports up to 1 MB/s write and 2 MB/s read, so more shards allow the stream to handle higher data volumes, reducing the likelihood of throttling and dropped records at the stream level.
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 number of shards in the Kinesis data stream.
Why this is correct
More shards increase parallelism and throughput.
- ✓
Set a reserved concurrency on the Lambda function to prevent other functions from using its capacity.
Why this is correct
Reserved concurrency guarantees the function has enough concurrency.
- ✗
Add a Dead Letter Queue to the Lambda function to capture failed records.
Why it's wrong here
A DLQ captures failures but does not prevent throttling or dropping.
- ✗
Decrease the batch size in the Lambda event source mapping.
Why it's wrong here
Decreasing batch size reduces throughput, worsening the problem.
- ✗
Increase the Kinesis stream's retention period to 7 days.
Why it's wrong here
Retention period does not affect throttling or Lambda processing.
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
Related to this question
About these practice questions
This MLS-C01 question is part of Courseiva's 1,672-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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.