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Data Engineering →hardMultiple ChoiceObjective-mapped

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 data engineering team is building a real-time data pipeline using Amazon Kinesis Data Streams with AWS Lambda for processing. The pipeline ingests clickstream data from a mobile app. The team notices that occasionally, a Lambda function fails due to a transient error, and the failed record is not retried, leading to data loss. The Lambda function is configured with a batch size of 100 and a maximum retry count of 0. The team wants to ensure that all records are processed successfully, even if transient failures occur. They also want to minimize the impact of poison pill records that could block processing. Which combination of actions should the team take to address this issue?

Clue words in this question

Noticing these words before you look at the options changes how you read each choice.

Clue: "minimum / minimize"
Why it matters: Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

A
Set the maximum retry count to 5 and configure a dead-letter queue on the Lambda function to capture failed records after retries.
Why wrong: Lambda's built-in DLQ is for asynchronous invocations, not for Kinesis event source mappings. Need a custom destination.
B
Switch to using Amazon Kinesis Data Firehose to buffer data and use AWS Lambda for transformation with built-in retry logic.
Why wrong: Firehose does not provide per-record processing and may introduce latency.
C
Set the maximum retry count to 5, configure an on-failure destination Amazon SQS queue, and set up a dead-letter queue on that SQS queue for poison pills.
This provides retries and isolates poison pills without blocking the main stream.
D
Reduce the batch size to 1 and increase the Lambda function timeout to handle transient errors.
Why wrong: Reducing batch size may cause throttling and does not handle poison pills.

Full breakdown with real-world context →

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

✓

Set the maximum retry count to 5, configure an on-failure destination Amazon SQS queue, and set up a dead-letter queue on that SQS queue for poison pills.

To address the issue of data loss due to transient errors and poison pill records, the team should increase the Lambda function's maximum retry count to 5 to allow retries on transient failures. However, even with retries, some records may fail repeatedly (poison pills) which can block the shard if not handled. Configuring an on-failure destination (such as an Amazon SQS queue) on the Lambda function sends all records that failed after retries to that queue. Then, by setting up a dead-letter queue on that SQS queue, poison pill records are isolated and can be examined or reprocessed separately, preventing them from blocking the main processing pipeline. Option A is incorrect because a dead-letter queue on Lambda alone is not sufficient – it captures failures after retries if configured, but the key is to also have an on-failure destination to offload failures. Option B is incorrect because Kinesis Data Firehose is designed for streaming data to destinations like S3, not for real-time per-record Lambda processing with built-in retry logic; it would change the architecture. Option D is incorrect because reducing batch size to 1 would increase costs and processing time, and may not fully resolve transient errors or poison pill issues.

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.

✗
Set the maximum retry count to 5 and configure a dead-letter queue on the Lambda function to capture failed records after retries.
Why it's wrong here
Lambda's built-in DLQ is for asynchronous invocations, not for Kinesis event source mappings. Need a custom destination.
✗
Switch to using Amazon Kinesis Data Firehose to buffer data and use AWS Lambda for transformation with built-in retry logic.
Why it's wrong here
Firehose does not provide per-record processing and may introduce latency.
✓
Set the maximum retry count to 5, configure an on-failure destination Amazon SQS queue, and set up a dead-letter queue on that SQS queue for poison pills.
Why this is correct
This provides retries and isolates poison pills without blocking the main stream.
Clue confirmation
The clue word "minimum / minimize" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reduce the batch size to 1 and increase the Lambda function timeout to handle transient errors.
Why it's wrong here
Reducing batch size may cause throttling and does not handle poison pills.

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 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.

Visual reference

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

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: Set the maximum retry count to 5, configure an on-failure destination Amazon SQS queue, and set up a dead-letter queue on that SQS queue for poison pills. — To address the issue of data loss due to transient errors and poison pill records, the team should increase the Lambda function's maximum retry count to 5 to allow retries on transient failures. However, even with retries, some records may fail repeatedly (poison pills) which can block the shard if not handled. Configuring an on-failure destination (such as an Amazon SQS queue) on the Lambda function sends all records that failed after retries to that queue. Then, by setting up a dead-letter queue on that SQS queue, poison pill records are isolated and can be examined or reprocessed separately, preventing them from blocking the main processing pipeline. Option A is incorrect because a dead-letter queue on Lambda alone is not sufficient – it captures failures after retries if configured, but the key is to also have an on-failure destination to offload failures. Option B is incorrect because Kinesis Data Firehose is designed for streaming data to destinations like S3, not for real-time per-record Lambda processing with built-in retry logic; it would change the architecture. Option D is incorrect because reducing batch size to 1 would increase costs and processing time, and may not fully resolve transient errors or poison pill issues.

What should I do if I get this MLS-C01 question wrong?

Are there clue words in this question I should notice?

Yes — watch for: "minimum / minimize". Asks for the least resource use — fewest addresses, smallest subnet, lowest overhead. Eliminate over-provisioned options even if they would technically work.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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