- A
Increase the record size to 1 MB to reduce the number of records
Why wrong: Record size is determined by the data source; artificially increasing it is not feasible.
- B
Switch to Kinesis Data Firehose instead of Data Streams
Why wrong: Firehose does not support Lambda as a direct consumer with the same flexibility.
- C
Request a limit increase for the Lambda function's concurrent execution limit
This directly alleviates throttling by allowing more concurrent executions.
- D
Increase the number of shards in the Kinesis stream
Why wrong: More shards increase parallelism but also increase Lambda invocations, potentially worsening throttling.
- E
Increase the batch size in the Lambda event source mapping
Larger batches mean fewer Lambda invocations, reducing concurrency.
Quick Answer
The answer is to increase the Lambda concurrency limit and increase the batch size in the event source mapping. When a Lambda function consumes from Kinesis Data Streams, throttling occurs because the default per-region concurrency limit is too low to handle the number of shards, or because each shard triggers too many invocations. Increasing the concurrency limit directly removes the cap on parallel executions, while increasing the batch size allows each invocation to process more records (up to 10,000 or 6 MB), reducing the total number of invocations per shard. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of Lambda’s synchronous invocation model with Kinesis—a common trap is choosing to add more shards, which actually increases the number of concurrent executions and worsens throttling. Remember the memory tip: “More per shard, less per second”—boost batch size to pack more records into each call, and raise the concurrency ceiling to let Lambda breathe.
MLS-C01 Data Engineering Practice Question
This MLS-C01 practice question tests your understanding of data engineering. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. 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 company is using Amazon Kinesis Data Streams with 10 shards to ingest clickstream data. Each record is approximately 50 KB. The data is consumed by a Lambda function that writes to DynamoDB. The Lambda function is experiencing throttling errors. Which TWO actions should the data engineer take to resolve the issue? (Choose TWO.)
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
Request a limit increase for the Lambda function's concurrent execution limit
Option A (increase shards) increases throughput but may not solve Lambda throttling. Option B (increase Lambda concurrency limit) directly addresses throttling. Option C (increase batch size) reduces number of Lambda invocations. Option D (use Firehose) changes architecture. Option E (increase record size) is irrelevant. The correct answers are B and C because they reduce the number of concurrent Lambda executions and increase efficiency.
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 record size to 1 MB to reduce the number of records
Why it's wrong here
Record size is determined by the data source; artificially increasing it is not feasible.
- ✗
Switch to Kinesis Data Firehose instead of Data Streams
Why it's wrong here
Firehose does not support Lambda as a direct consumer with the same flexibility.
- ✓
Request a limit increase for the Lambda function's concurrent execution limit
Why this is correct
This directly alleviates throttling by allowing more concurrent executions.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the number of shards in the Kinesis stream
Why it's wrong here
More shards increase parallelism but also increase Lambda invocations, potentially worsening throttling.
- ✓
Increase the batch size in the Lambda event source mapping
Why this is correct
Larger batches mean fewer Lambda invocations, reducing concurrency.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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: Request a limit increase for the Lambda function's concurrent execution limit — Option A (increase shards) increases throughput but may not solve Lambda throttling. Option B (increase Lambda concurrency limit) directly addresses throttling. Option C (increase batch size) reduces number of Lambda invocations. Option D (use Firehose) changes architecture. Option E (increase record size) is irrelevant. The correct answers are B and C because they reduce the number of concurrent Lambda executions and increase efficiency.
What should I do if I get this MLS-C01 question wrong?
Identify which MLS-C01 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jun 20, 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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