- A
Increase the Lambda function memory to 3,000 MB to reduce the execution time below 100 ms.
Why wrong: Memory increase may reduce time but not enough to avoid throttling at high invocation rates.
- B
Use Amazon Kinesis Data Firehose instead of Lambda to load data directly into DynamoDB.
Why wrong: Kinesis Data Firehose does not support DynamoDB as a destination.
- C
Reduce the Lambda batch size to 10 so that each invocation processes fewer records, reducing the time per invocation.
Why wrong: This increases invocations per second to 1,000, which would exceed the concurrency limit of 1,000 if each takes 200 ms.
- D
Increase the number of shards in the Kinesis Data Stream to 10 and set the Lambda batch size to 100.
With 10 shards and batch size 100, at most 10 concurrent Lambda invocations, well within limits.
Quick Answer
The correct approach is to increase the number of shards in the Kinesis Data Stream to 10 and set the Lambda batch size to 100. This works because each shard processes one batch at a time, so with 10 shards and a batch size of 100, the maximum concurrent Lambda executions is only 10—well within the default 1,000 concurrency limit—while still handling 10,000 records per second (10 shards × 100 records per batch × 10 batches per second, given the 200 ms function duration). On the AWS Certified Machine Learning Specialty MLS-C01 exam, this question tests your understanding of Lambda concurrency tuning for Kinesis streams, specifically how shard count and batch size interact to prevent throttling. A common trap is assuming you can simply increase memory or reduce batch size, but that actually increases invocations per second and risks hitting concurrency limits. Memory tip: “Shards control concurrency, batches control throughput”—always match shard count to your desired concurrency ceiling.
MLS-C01 Data Engineering Practice Question
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 company is building a data pipeline to process streaming data from IoT devices. The data is ingested via Amazon Kinesis Data Streams. Each record is about 1 KB. The company wants to use AWS Lambda for real-time transformations and then store the results in Amazon DynamoDB. The expected throughput is 10,000 records per second. The Lambda function currently runs in about 200 ms. The company is concerned about Lambda concurrency limits and wants to ensure there are no throttling errors. The default concurrency limit for Lambda is 1,000. Which approach should the team take to handle the expected throughput without throttling?
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 to 10 and set the Lambda batch size to 100.
Option B is correct because increasing the shard count to 10 ensures that each shard can trigger a Lambda invocation concurrently, and with a batch size of 100, the number of concurrent Lambda executions is at most 10 (10 shards * 1 batch per shard). This stays well within the concurrency limit. Option A is incorrect because reducing batch size increases the number of invocations per second (10,000 / 10 = 1,000 invocations per second), which would exceed the concurrency limit if each invocation takes 200 ms. Option C is incorrect because Kinesis Data Firehose does not support Lambda for per-record transformations. Option D is incorrect because increasing memory does not affect concurrency limits.
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 Lambda function memory to 3,000 MB to reduce the execution time below 100 ms.
Why it's wrong here
Memory increase may reduce time but not enough to avoid throttling at high invocation rates.
- ✗
Use Amazon Kinesis Data Firehose instead of Lambda to load data directly into DynamoDB.
Why it's wrong here
Kinesis Data Firehose does not support DynamoDB as a destination.
- ✗
Reduce the Lambda batch size to 10 so that each invocation processes fewer records, reducing the time per invocation.
Why it's wrong here
This increases invocations per second to 1,000, which would exceed the concurrency limit of 1,000 if each takes 200 ms.
- ✓
Increase the number of shards in the Kinesis Data Stream to 10 and set the Lambda batch size to 100.
Why this is correct
With 10 shards and batch size 100, at most 10 concurrent Lambda invocations, well within limits.
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: Increase the number of shards in the Kinesis Data Stream to 10 and set the Lambda batch size to 100. — Option B is correct because increasing the shard count to 10 ensures that each shard can trigger a Lambda invocation concurrently, and with a batch size of 100, the number of concurrent Lambda executions is at most 10 (10 shards * 1 batch per shard). This stays well within the concurrency limit. Option A is incorrect because reducing batch size increases the number of invocations per second (10,000 / 10 = 1,000 invocations per second), which would exceed the concurrency limit if each invocation takes 200 ms. Option C is incorrect because Kinesis Data Firehose does not support Lambda for per-record transformations. Option D is incorrect because increasing memory does not affect concurrency limits.
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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