- A
Use Kinesis Firehose as a consumer of the stream, with a Lambda transformation to write to DynamoDB, and enable error handling.
Firehose buffers data, retries on failures, and decouples the producer from DynamoDB writes.
- B
Increase the Lambda function's reserved concurrency and provision more DynamoDB write capacity.
Why wrong: Increasing capacity may help temporarily but does not decouple the system; throttling can still occur.
- C
Place the Lambda function's output into an Amazon SQS queue, and have a second Lambda function write to DynamoDB.
Why wrong: SQS is not directly integrated with Kinesis; additional components increase complexity.
- D
Use Kinesis Data Analytics to process the stream and write results directly to DynamoDB.
Why wrong: Kinesis Data Analytics does not have a built-in DynamoDB sink; it can output to Firehose or Lambda.
Quick Answer
The correct choice is to use Kinesis Firehose as a consumer of the stream, with a Lambda transformation to write to DynamoDB, and enable error handling. This works because Firehose acts as a buffer between Kinesis Data Streams and DynamoDB, absorbing traffic spikes and providing built-in retry logic when ProvisionedThroughputExceededException occurs, effectively decoupling the write operation and improving resilience. On the AWS Certified Machine Learning Specialty MLS-C01 exam, this scenario tests your understanding of real-time data pipeline patterns and the trade-offs between direct Lambda consumption and buffered ingestion—a common trap is assuming Lambda alone can handle throttling by scaling, but the real bottleneck is DynamoDB’s provisioned capacity, not compute. Remember the mnemonic “Firehose buffers the blows” to recall that Firehose’s buffering and retry mechanism is the key to decoupling Kinesis writes to DynamoDB under load.
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 uses Kinesis Data Streams to ingest real-time sensor data. The data is consumed by a Lambda function that writes to DynamoDB. During peak hours, the Lambda function throws ProvisionedThroughputExceededException. The team wants to decouple the write operation and improve resilience. What should they do?
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 Kinesis Firehose as a consumer of the stream, with a Lambda transformation to write to DynamoDB, and enable error handling.
Option A is correct because Kinesis Firehose can buffer data and write to DynamoDB via Lambda, providing retry and decoupling. Option B is wrong because SQS does not integrate directly with Kinesis. Option C is wrong because Kinesis Data Analytics does not write to DynamoDB directly. Option D is wrong because Lambda is already being used; the issue is throughput, not compute.
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.
- ✓
Use Kinesis Firehose as a consumer of the stream, with a Lambda transformation to write to DynamoDB, and enable error handling.
Why this is correct
Firehose buffers data, retries on failures, and decouples the producer from DynamoDB writes.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the Lambda function's reserved concurrency and provision more DynamoDB write capacity.
Why it's wrong here
Increasing capacity may help temporarily but does not decouple the system; throttling can still occur.
- ✗
Place the Lambda function's output into an Amazon SQS queue, and have a second Lambda function write to DynamoDB.
Why it's wrong here
SQS is not directly integrated with Kinesis; additional components increase complexity.
- ✗
Use Kinesis Data Analytics to process the stream and write results directly to DynamoDB.
Why it's wrong here
Kinesis Data Analytics does not have a built-in DynamoDB sink; it can output to Firehose or Lambda.
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.
Trap categories for this question
Command / output trap
Kinesis Data Analytics does not have a built-in DynamoDB sink; it can output to Firehose or Lambda.
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 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.
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: Use Kinesis Firehose as a consumer of the stream, with a Lambda transformation to write to DynamoDB, and enable error handling. — Option A is correct because Kinesis Firehose can buffer data and write to DynamoDB via Lambda, providing retry and decoupling. Option B is wrong because SQS does not integrate directly with Kinesis. Option C is wrong because Kinesis Data Analytics does not write to DynamoDB directly. Option D is wrong because Lambda is already being used; the issue is throughput, not compute.
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.
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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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