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Question 390 of 1,786

Data Operations and Support →mediumMultiple ChoiceObjective-mapped

Quick Answer

The correct action is to modify the application to use PutRecordBatch with smaller batch sizes to stay within the 4 MB per-call limit. This LimitExceededException occurs because Kinesis Data Analytics writes to Firehose via PutRecord or PutRecordBatch calls, each of which has a hard payload cap—1 MB for single records and 4 MB for batch calls. Even though the delivery stream’s IncomingBytes and IncomingRecords are below provisioned limits, the per-call payload limit is independent of buffer size or interval settings. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding that Kinesis Data Analytics acts as a producer to Firehose, and the 4 MB PutRecordBatch limit is a common trap—candidates often mistakenly blame buffer settings or source stream throttling. A helpful memory tip: think of the Firehose per-call limit as a “single-serve” constraint—no matter how big your buffer bucket is, each batch you pour must fit in a 4 MB cup.

DEA-C01 Data Operations and Support Practice Question

This DEA-C01 practice question tests your understanding of data operations and support. 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.

Your team uses Amazon Kinesis Data Analytics to process real-time streaming data from an Amazon Kinesis Data Stream. The application calculates windowed aggregations and writes results to an Amazon S3 bucket using a delivery stream. Recently, the application has been failing with a 'LimitExceededException' when writing to the delivery stream. You have checked the CloudWatch metrics and see that the IncomingBytes and IncomingRecords for the delivery stream are well below the provisioned limits. The delivery stream has a buffer size of 5 MB and a buffer interval of 60 seconds. The application generates about 500 records per second, each about 1 KB. What is the most likely cause and correct action?

Clue words in this question

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

Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

Question 1mediummultiple choice

Full question →

A
Increase the number of shards in the Kinesis Data Stream to reduce the load on the application.
Why wrong: The error is from the delivery stream, not the data stream.
B
Modify the application to use PutRecordBatch with smaller batch sizes to stay within the 4 MB per-call limit.
The LimitExceededException on Firehose is often due to exceeding the 4 MB per PutRecordBatch call. Reducing batch size fixes it.
C
Reduce the buffer interval of the delivery stream to 30 seconds to flush data more frequently.
Why wrong: This does not affect per-call payload limits.
D
Increase the buffer size of the delivery stream to 10 MB to accommodate larger writes.
Why wrong: Buffer size is for buffering, not for per-record payload limits. The error is likely due to the PutRecordBatch limit.

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

✓

Modify the application to use PutRecordBatch with smaller batch sizes to stay within the 4 MB per-call limit.

Option B is correct because Kinesis Data Analytics writes to Firehose through a PutRecord or PutRecordBatch call. Each call has a maximum payload size of 1 MB (for PutRecord) or 4 MB (for PutRecordBatch). If the application uses PutRecordBatch and the total payload exceeds 4 MB, it gets a LimitExceededException. Increasing the buffer size or interval does not affect the per-call limit. Option A is wrong because the stream is not the source of the error. Option C is wrong because the buffer settings are not causing the per-call limit. Option D is wrong because the data size is small.

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 to reduce the load on the application.
Why it's wrong here
The error is from the delivery stream, not the data stream.
✓
Modify the application to use PutRecordBatch with smaller batch sizes to stay within the 4 MB per-call limit.
Why this is correct
The LimitExceededException on Firehose is often due to exceeding the 4 MB per PutRecordBatch call. Reducing batch size fixes it.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
Reduce the buffer interval of the delivery stream to 30 seconds to flush data more frequently.
Why it's wrong here
This does not affect per-call payload limits.
✗
Increase the buffer size of the delivery stream to 10 MB to accommodate larger writes.
Why it's wrong here
Buffer size is for buffering, not for per-record payload limits. The error is likely due to the PutRecordBatch limit.

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 media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.

What to study next

Got this wrong? Here's your next step.

Identify which DEA-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 DEA-C01 question test?

Data Operations and Support — This question tests Data Operations and Support — Read the scenario before looking for a memorised answer..

What is the correct answer to this question?

The correct answer is: Modify the application to use PutRecordBatch with smaller batch sizes to stay within the 4 MB per-call limit. — Option B is correct because Kinesis Data Analytics writes to Firehose through a PutRecord or PutRecordBatch call. Each call has a maximum payload size of 1 MB (for PutRecord) or 4 MB (for PutRecordBatch). If the application uses PutRecordBatch and the total payload exceeds 4 MB, it gets a LimitExceededException. Increasing the buffer size or interval does not affect the per-call limit. Option A is wrong because the stream is not the source of the error. Option C is wrong because the buffer settings are not causing the per-call limit. Option D is wrong because the data size is small.

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

Are there clue words in this question I should notice?

Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.

What is the key concept behind this question?

Read the scenario before looking for a memorised answer.

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This DEA-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 DEA-C01 exam.