- A
Increase the number of KCL workers to match the number of shards.
Multiple workers can process shards in parallel, reducing per-worker load.
- B
Enable enhanced fan-out for the consumer.
Enhanced fan-out provides dedicated read throughput, eliminating read throttling.
- C
Decrease the checkpoint interval to reduce checkpointing overhead.
Why wrong: More frequent checkpointing increases DynamoDB writes and can cause delays.
- D
Increase the KCL maxRecords parameter to process more records per call.
Processing more records per GetRecords call reduces the number of API calls and improves throughput.
- E
Increase the number of shards in the stream.
Why wrong: More shards increase the write capacity but also increase the number of shards the consumer must process, worsening the issue.
Quick Answer
The answer is to increase the number of workers, increase the KCL maxRecords parameter, and enable enhanced fan-out. These three actions directly address Kinesis Client Library worker performance scaling by distributing the processing load and reducing per-record overhead. A single worker processing all 10 shards creates a bottleneck; adding workers allows each to handle fewer shards, improving parallelism. Increasing maxRecords reduces the frequency of API calls, letting the worker batch more records per retrieval, which lowers latency and checkpointing delays. Enhanced fan-out dedicates 2 MB/s of read throughput per consumer, eliminating read throttling from the default shared throughput. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of KCL worker architecture and the trade-offs between parallelism and API efficiency. A common trap is confusing shard count with consumer performance—adding shards only increases the load, not the throughput. Remember the mnemonic “W-M-E” for Workers, MaxRecords, and Enhanced fan-out to recall the three scaling levers.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 engineer is troubleshooting a Kinesis Data Streams consumer application that is falling behind. The stream has 10 shards and is receiving 5 MB/s of data. The consumer uses the Kinesis Client Library (KCL) with a single worker. The worker is processing all 10 shards but is experiencing high latency and checkpointing delays. Which THREE actions should the engineer take to improve consumer performance? (Select THREE.)
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 KCL workers to match the number of shards.
Option A (increase number of workers) allows shard distribution across multiple workers, improving parallelism. Option D (increase KCL maxRecords per call) reduces the number of API calls, improving throughput. Option E (enable enhanced fan-out) dedicates throughput to the consumer, reducing read throttling. Option B is wrong because increasing shards would increase the load on the consumer. Option C is wrong because reducing the checkpoint interval would cause more frequent checkpointing, potentially increasing delays.
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 KCL workers to match the number of shards.
Why this is correct
Multiple workers can process shards in parallel, reducing per-worker load.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
Enable enhanced fan-out for the consumer.
Why this is correct
Enhanced fan-out provides dedicated read throughput, eliminating read throttling.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Decrease the checkpoint interval to reduce checkpointing overhead.
Why it's wrong here
More frequent checkpointing increases DynamoDB writes and can cause delays.
- ✓
Increase the KCL maxRecords parameter to process more records per call.
Why this is correct
Processing more records per GetRecords call reduces the number of API calls and improves throughput.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the number of shards in the stream.
Why it's wrong here
More shards increase the write capacity but also increase the number of shards the consumer must process, worsening the issue.
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 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 Ingestion and Transformation — This question tests Data Ingestion and Transformation — 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 KCL workers to match the number of shards. — Option A (increase number of workers) allows shard distribution across multiple workers, improving parallelism. Option D (increase KCL maxRecords per call) reduces the number of API calls, improving throughput. Option E (enable enhanced fan-out) dedicates throughput to the consumer, reducing read throttling. Option B is wrong because increasing shards would increase the load on the consumer. Option C is wrong because reducing the checkpoint interval would cause more frequent checkpointing, potentially increasing delays.
What should I do if I get this DEA-C01 question wrong?
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.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Same concept, more angles
1 more ways this is tested on DEA-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A data engineer is troubleshooting a Kinesis Data Streams application that is experiencing high latency. The stream has 2 shards. The application is using a single Kinesis Client Library (KCL) worker to process all shards. Which change will MOST likely reduce latency?
hard- A.Increase the number of shards to 4.
- ✓ B.Deploy multiple KCL workers to process shards in parallel.
- C.Use a larger instance type for the Kinesis stream.
- D.Decrease the number of shards to 1.
Why B: Option D is correct because using multiple KCL workers, one per shard, allows parallel processing of each shard, reducing latency. Option A is incorrect because increasing shard count would increase capacity but not necessarily reduce latency if the processing is bottlenecked by a single worker. Option B is incorrect because decreasing shard count would reduce parallelism. Option C is incorrect because the KCL worker runs in the application, not in Kinesis.
Last reviewed: Jun 20, 2026
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.
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