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Data Operations and SupportmediumMultiple ChoiceObjective-mapped

DEA-C01 Data Operations and Support Practice Question

A company uses Amazon DynamoDB as a data store for a real-time dashboard application. The application performs point lookups and range queries on a table that has a partition key and sort key. The table uses on-demand capacity mode. Recently, the application's response time has increased, and CloudWatch metrics show high 'ThrottledRequests' for the table. The application uses the AWS SDK with default retry settings. The data access pattern is read-heavy with occasional spikes. What is the most effective way to reduce throttling?

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 with jitter in the application code.

DynamoDB on-demand mode can throttle requests when traffic exceeds the table's previous peak by more than double. Implementing exponential backoff with jitter in the application code allows retries to spread out and succeed without overwhelming the table. Option A is incorrect because switching to provisioned capacity requires accurate capacity planning and may still throttle during unexpected spikes. Option B is incorrect because DAX caches frequently read items, reducing read load, but it does not directly address throttling caused by exceeding the table's throughput limits; it also adds cost and complexity. Option C is incorrect because increasing read capacity units applies only to provisioned capacity mode, not on-demand.

Answer analysis

Option-by-option breakdown

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

  • Switch the table to provisioned capacity and set the read capacity units to a high value.

    Why it's wrong here

    On-demand is designed for spiky workloads; switching to provisioned may lead to underutilization or still throttle if spikes exceed provisioned capacity.

  • Enable DynamoDB Accelerator (DAX) to cache frequently read items.

    Why it's wrong here

    DAX reduces read load but does not help with write throttling; also adds cost.

  • Increase the read capacity units to a higher value.

    Why it's wrong here

    On-demand mode doesn't use read capacity units; this option is not applicable.

  • Implement exponential backoff with jitter in the application code.

    Why this is correct

    Retries with backoff reduce the rate of requests during throttling, allowing the table to recover.

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