AWS Certified Data Engineer Associate DEA-C01 Practice Question
An ecommerce company ingests clickstream events from thousands of websites. Events arrive in unpredictable surges, occasionally 10-20 times higher than normal. The events are written directly to a DynamoDB table configured for provisioned capacity with auto scaling (min 200 WCU, max 2,000 WCU). During surges, the application receives ProvisionedThroughputExceededException errors. The team wants to eliminate throttling while keeping costs low and avoiding additional infrastructure. Which change will meet these goals?
Increase the auto scaling maximum write capacity to 10,000 WCU and set the target utilization to 90%.
Write incoming events to an Amazon SQS queue and invoke an AWS Lambda function to batch insert 25 items at a time.
Switching the table to on-demand capacity mode removes the need to provision or scale write capacity in advance. DynamoDB automatically accommodates sudden traffic bursts and charges only for actual requests, so write throttling is eliminated without raising baseline capacity or adding buffering components. Adaptive capacity only redistributes existing throughput and does not prevent table-level throttling. Raising the auto-scaling maximum still leaves a lag before capacity increases and can be wasteful during normal traffic. Adding SQS and Lambda introduces extra services but does not solve the underlying write-capacity limit on the table.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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