DEA-C01 Data Operations and Support Practice Question
A company uses Amazon Kinesis Data Analytics for Apache Flink to process streaming data. The application reads from a Kinesis data stream and writes results to an S3 bucket. The application is consistently running out of memory and failing. The operator has already increased the Parallelism and TaskManager memory. What is the next BEST step to troubleshoot?
⚠ Common exam trap
DEA-C01 often tests the impulse to keep scaling resources (parallelism, memory) without first enabling metrics, when the correct troubleshooting step is to gain visibility into heap and checkpoint behavior.
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
✓
Enable Apache Flink metrics in Amazon CloudWatch to monitor heap and checkpoint details
When a Flink application on Kinesis Data Analytics runs out of memory despite increased parallelism and TaskManager memory, the next best step is to enable Apache Flink metrics in CloudWatch to observe heap usage, garbage collection, and checkpoint behavior. These metrics reveal whether the issue is memory leaks, backpressure, or state growth. Without observability, further tuning is guesswork.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the processing mode from exactly-once to at-least-once
Why it's wrong here
At-least-once processing removes checkpointing and two-phase commit state, but the stem's out-of-memory failures come from unbounded operator state or buffering, not the checkpointing mode. It is tempting because exactly-once carries overhead, yet switching modes risks duplicate S3 writes without addressing heap growth.
- ✗
Reduce the number of shards in the source stream
Why it's wrong here
Shard count governs source parallelism and read throughput; reducing shards lowers ingestion capacity and does nothing to relieve TaskManager heap pressure. It is tempting because fewer shards mean less concurrent processing, but the memory exhaustion stems from operator state or buffering, not shard count.
- ✓
Enable Apache Flink metrics in Amazon CloudWatch to monitor heap and checkpoint details
Why this is correct
Enabling Flink metrics in CloudWatch exposes heap usage, garbage-collection pressure and checkpoint behaviour, revealing whether state growth or backpressure—not raw parallelism—causes the out-of-memory failures. Since TaskManager memory and parallelism were already raised without success, these per-operator metrics identify the actual bottleneck before further resource changes.
- ✗
Increase the buffer timeout for the S3 sink
Why it's wrong here
Buffer timeout controls how long records wait before flushing to S3; extending it holds more data in the sink buffer and increases, not reduces, memory pressure. It is tempting because batching improves S3 write efficiency, but the failure is heap exhaustion, which longer buffering worsens.
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 |
Go deeper
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Amazon Web Services exam blueprint
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.