AWS Certified Data Engineer Associate DEA-C01 Practice Question
A company ingests clickstream events into an Amazon DynamoDB table. Traffic remains near zero most of the day but bursts to 40,000 writes per second during marketing campaigns. Analysts query events by userId and timestamp range. Provisioned capacity with auto scaling causes throttling and wasted spend. Which configuration best meets the performance and cost requirements with minimal administration?
Add a DynamoDB Accelerator (DAX) cluster in front of the table to cache hot items.
Triple the provisioned write capacity and reduce the auto-scaling cooldown period to 30 seconds.
Enable DynamoDB Streams and invoke an AWS Lambda function to batch writes into Amazon S3.
Convert the table and all global secondary indexes to on-demand capacity mode.
Switching the table and any global secondary indexes to on-demand capacity mode removes the need to provision or scale capacity manually. DynamoDB automatically accommodates sudden traffic spikes (up to tens of thousands of requests per second) and charges only for the read and write requests actually made, eliminating throttling during peaks and cost during idle periods. Simply raising provisioned capacity or tweaking auto-scaling still incurs idle cost and requires tuning. DAX improves read latency but does not increase write throughput. DynamoDB Streams with Lambda off-loads data elsewhere but leaves the original write traffic and throttling issues unresolved.
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AWS Certified Data Engineer Associate DEA-C01
Data Store Management
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