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Data Operations and SupportmediumMultiple ChoiceObjective-mapped

DEA-C01 Data Operations and Support Practice Question

A company runs a data pipeline that uses AWS Glue to process data from an Amazon DynamoDB table and write results to Amazon S3. The Glue job runs on a schedule every hour. Recently, the job started failing intermittently with 'ProvisionedThroughputExceededException' errors from DynamoDB. What is the BEST solution?

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

Implement exponential backoff and retries in the Glue job for DynamoDB operations.

Implementing exponential backoff and retries in the Glue job is a best practice to handle transient throttling errors from DynamoDB such as ProvisionedThroughputExceededException. This approach allows the job to automatically retry failed operations with increasing delays, reducing the likelihood of sustained failures without requiring changes to the DynamoDB table's provisioned capacity. Option A is incorrect because DynamoDB Accelerator (DAX) is an in-memory cache that can reduce read traffic for cached items, but it does not guarantee elimination of ProvisionedThroughputExceeded exceptions, especially for read operations that are not cached or when the underlying issue is read throughput limits. Option B is incorrect because running the job less frequently does not address the intermittent throttling; the job may still encounter the same error when it runs. Option D is incorrect because, although increasing read capacity units could directly address read throttling, it is not the most cost-effective or best practice for dealing with occasional throttling. The recommended approach is to first implement exponential backoff and retries, only increasing provisioned capacity if throttling persists. Moreover, the ProvisionedThroughputExceededException in this scenario is due to read throughput limits, and increasing write capacity would not help.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Use DynamoDB Accelerator (DAX) to reduce read latency.

    Why it's wrong here

    DAX does not prevent throttling on the table itself.

  • Change the Glue job schedule to run every 2 hours.

    Why it's wrong here

    This reduces frequency but does not handle spikes.

  • Implement exponential backoff and retries in the Glue job for DynamoDB operations.

    Why this is correct

    Exponential backoff handles throttling gracefully.

  • Increase the read capacity units of the DynamoDB table.

    Why it's wrong here

    This may not be needed if the table is properly sized.

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.