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Data Operations and SupporthardMultiple ChoiceObjective-mapped

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?

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

Enabling Apache Flink metrics in Amazon CloudWatch provides visibility into heap usage, checkpoint sizes, and backpressure, which can help diagnose the root cause of memory failures. After increasing parallelism and TaskManager memory without success, the next best step is to monitor these metrics to identify the specific bottleneck. Option A changes processing semantics from exactly-once to at-least-once, which can reduce overhead but does not help diagnose the memory issue and may alter data delivery guarantees. Option B reduces the number of shards in the source stream, which decreases throughput and might not address the underlying memory consumption. Option D increases the buffer timeout for the S3 sink, which could accumulate more data in memory before writing, potentially worsening the memory problem.

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

    This changes semantics but not memory.

  • Reduce the number of shards in the source stream

    Why it's wrong here

    This reduces throughput but not necessarily memory per task.

  • Enable Apache Flink metrics in Amazon CloudWatch to monitor heap and checkpoint details

    Why this is correct

    Detailed metrics help identify root cause of OOM.

  • Increase the buffer timeout for the S3 sink

    Why it's wrong here

    This reduces latency but not memory consumption.

Quick reference

AWS S3 Storage Class Comparison

Storage ClassMin DurationRetrievalUse Case
S3 StandardNoneImmediateFrequently accessed data
S3 Standard-IA30 daysImmediateInfrequent access, rapid retrieval
S3 One Zone-IA30 daysImmediateNon-critical infrequent data
S3 Intelligent-TieringNoneImmediate–hoursUnknown or changing access patterns
S3 Glacier Instant90 daysMillisecondsArchive with instant retrieval
S3 Glacier Flexible90 daysMinutes–hoursArchive, flexible retrieval
S3 Glacier Deep Archive180 daysHoursLong-term compliance archive

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Written by Johnson Ajibi, MSc IT Security

Senior Network & Security Engineer · founder of Courseiva

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.