The answer is to increase the parallelism of the Flink application. This is the most effective action because high latency in Flink often stems from a processing bottleneck where the application cannot consume data as fast as it arrives. By increasing parallelism, you distribute the workload across more parallel subtasks, allowing the application to process records concurrently and keep up with the incoming data rate from the Kinesis stream. On the AWS Certified Data Engineer Associate DEA-C01 exam, this scenario tests your understanding of how Flink’s parallelism maps to Kinesis shard count—a common trap is to add more shards, but the bottleneck is on the processing side, not the source. Remember, parallelism is the number of concurrent operators, not the number of shards. A useful memory tip: “Parallelism processes, shards source”—when latency climbs, boost the parallelism before touching the stream.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. 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 uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application reads from a Kinesis stream with 10 shards and writes to an S3 bucket. The application is experiencing high latency. Analysis shows that the application is not keeping up with the incoming data rate. Which action would MOST effectively reduce latency?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the Parallelism of the Flink application
Increasing the parallelism of the Flink application allows it to process more data concurrently. This directly addresses the processing bottleneck.
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 stream
Why it's wrong here
More shards increase input rate; if the application can't keep up, it worsens latency.
✓
Increase the Parallelism of the Flink application
Why this is correct
Higher parallelism allows more concurrent processing.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable exactly-once delivery to S3
Why it's wrong here
Exactly-once adds overhead and may increase latency.
✗
Use a larger Kinesis Data Analytics application (increase KPU)
Why it's wrong here
While increasing KPU can help, parallelism is more direct; KPU may be limited by default.
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.
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 Parallelism of the Flink application — Increasing the parallelism of the Flink application allows it to process more data concurrently. This directly addresses the processing bottleneck.
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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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.
Question Discussion
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