- A
Increase the parallelism of the Flink application.
Why wrong: Increasing parallelism without diagnosing the cause may lead to over-provisioning or masking the real issue.
- B
Monitor CPU and memory utilization of the Flink application using Amazon CloudWatch metrics.
Resource exhaustion is a common cause of checkpoint failures; monitoring helps identify if scaling is needed.
- C
Switch to the Kinesis Client Library (KCL) for checkpointing.
Why wrong: KCL is for Kinesis Data Streams consumers, not for Flink applications using Data Analytics.
- D
Increase the checkpoint interval to reduce checkpoint frequency.
Why wrong: This reduces overhead but does not diagnose the root cause of failures.
Quick Answer
The answer is to monitor CPU and memory utilization of the Flink application using Amazon CloudWatch metrics. This is the correct first step because checkpoint failures in Apache Flink are most commonly caused by resource bottlenecks—when the task manager runs out of heap space or CPU cycles, it cannot complete the snapshot of state within the configured timeout, leading to failure and increasing processing delay. On the AWS Certified Data Engineer Associate DEA-C01 exam, this question tests your ability to follow a systematic diagnostic workflow rather than jumping to tuning parameters like parallelism or checkpoint interval, which are common traps. The exam emphasizes that resource monitoring is the foundational triage step before making any configuration changes. Remember the memory tip: “Check resources first, tune later”—if the engine is starved, no amount of scheduling or parallelism adjustments will fix the root cause.
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 company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application reads from a Kinesis data stream, performs a 1-minute tumbling window aggregation, and writes results to an S3 bucket. Recently, the application started experiencing checkpoint failures and increasing processing delay. Which action should the engineer take FIRST to diagnose the issue?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"first"Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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
Monitor CPU and memory utilization of the Flink application using Amazon CloudWatch metrics.
Option B is correct because checkpoint failures are often due to insufficient resources (CPU/memory) for the Flink job. Monitoring CPU and memory utilization via CloudWatch metrics directly helps identify resource bottlenecks. Option A (checkpoint interval) might help but is not diagnostic. Option C (parallelism) is a tuning step. Option D (KCL) is not relevant for Flink. The first step is to check resource utilization.
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 parallelism of the Flink application.
Why it's wrong here
Increasing parallelism without diagnosing the cause may lead to over-provisioning or masking the real issue.
- ✓
Monitor CPU and memory utilization of the Flink application using Amazon CloudWatch metrics.
Why this is correct
Resource exhaustion is a common cause of checkpoint failures; monitoring helps identify if scaling is needed.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Switch to the Kinesis Client Library (KCL) for checkpointing.
Why it's wrong here
KCL is for Kinesis Data Streams consumers, not for Flink applications using Data Analytics.
- ✗
Increase the checkpoint interval to reduce checkpoint frequency.
Why it's wrong here
This reduces overhead but does not diagnose the root cause of failures.
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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Data Ingestion and Transformation — study guide chapter
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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: Monitor CPU and memory utilization of the Flink application using Amazon CloudWatch metrics. — Option B is correct because checkpoint failures are often due to insufficient resources (CPU/memory) for the Flink job. Monitoring CPU and memory utilization via CloudWatch metrics directly helps identify resource bottlenecks. Option A (checkpoint interval) might help but is not diagnostic. Option C (parallelism) is a tuning step. Option D (KCL) is not relevant for Flink. The first step is to check resource utilization.
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.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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 company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The Flink application reads from a Kinesis Data Streams source, performs aggregations, and writes results to Amazon S3. The application is experiencing high checkpoint failures, and the processing lag is increasing. The data volume is 50 MB/s with an average record size of 1 KB. Which TWO actions would improve checkpoint reliability and reduce lag? (Choose TWO.)
hard- A.Decrease the checkpoint interval to complete checkpoints faster.
- B.Replace the S3 sink with Kinesis Data Firehose.
- C.Decrease the parallelism of the Flink application.
- ✓ D.Increase the checkpoint interval in the Flink configuration.
- ✓ E.Increase the number of Kinesis Processing Units (KPUs) for the application.
Why D: Options A and D are correct. Increase the checkpoint interval to reduce frequency, and increase parallelism with more KPUs. Option B is wrong because reducing parallelism would worsen lag. Option C is wrong because decreasing checkpoint interval increases failures. Option E is wrong because Kinesis Data Firehose is not a direct solution to checkpoint failures.
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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