- A
Increase the number of shards in the Kinesis data stream.
More shards increase parallelism and throughput.
- B
Set a reserved concurrency on the Lambda function to prevent other functions from using its capacity.
Reserved concurrency guarantees the function has enough concurrency.
- C
Add a Dead Letter Queue to the Lambda function to capture failed records.
Why wrong: A DLQ captures failures but does not prevent throttling or dropping.
- D
Decrease the batch size in the Lambda event source mapping.
Why wrong: Decreasing batch size reduces throughput, worsening the problem.
- E
Increase the Kinesis stream's retention period to 7 days.
Why wrong: Retention period does not affect throttling or Lambda processing.
Question 1,631 of 1,755
Fix Kinesis Lambda Throttling and Dropped Records
This MLS-C01 practice question tests your understanding of data engineering. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
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.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often 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.
Detailed technical explanation
How to think about this question
Kinesis Data Streams uses shard-level throughput limits; when the aggregate write rate exceeds the shard capacity, the stream returns ProvisionedThroughputExceeded exceptions. Lambda's event source mapping polls each shard with a single concurrent batch, so insufficient shards limit parallelism and can cause Lambda to fall behind, leading to record age-based expiration. Setting reserved concurrency ensures the Lambda function has guaranteed capacity, preventing other functions from starving it of execution slots.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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 |
What to study next
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FAQ
Questions learners often ask
What does this MLS-C01 question test?
Data Engineering — This question tests Data Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: 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.
What should I do if I get this MLS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
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.
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