AWS Certified Data Engineer Associate DEA-C01 Practice Question
An analytics team uses an S3 event notification to invoke a Python Lambda function that enriches each uploaded JSON file. A nightly batch uploads about 3,000 objects within 5 minutes, but invocations are throttled because the account concurrency limit is 1,000 and other functions consume most of it. The team must ensure all objects are processed within the 5-minute window without affecting other functions. What should they do?
Increase the function's memory size to shorten duration and rely on Lambda's burst concurrency to clear the backlog.
Enable 3,000 units of provisioned concurrency for the function during the batch window.
Send S3 events to an SQS queue and invoke the Lambda function with a batch size of 10 and the default concurrency settings.
Configure a reserved concurrency of 3,000 for the function and request an account concurrency limit increase to at least 3,000.
Reserved concurrency dedicates a pool of executions to one function and prevents other functions from using that capacity. Setting reserved concurrency to 3,000 guarantees the nightly load can run without throttling while isolating other functions from impact. Because reserved (and provisioned) concurrency counts toward the account quota, the team must request a matching account-level concurrency increase. Provisioned concurrency would also need the same quota increase and would incur hourly charges even when the function is idle. Adjusting memory or switching to SQS does not eliminate the concurrency bottleneck and still risks throttling.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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