AWS Certified Data Engineer Associate DEA-C01 Practice Question
An e-commerce company collects 5 MB/sec of JSON clickstream events from hundreds of browsers. The engineering team must ingest the data into Amazon S3 in near real time and be able to replay up to 24 hours of events if downstream processing fails. Operations effort must remain low. Which solution meets these requirements most cost-effectively?
Send the events directly to an Amazon Kinesis Data Firehose delivery stream configured to deliver to the S3 bucket.
Create an Amazon Kinesis Data Stream with 24-hour retention, provision five shards for 5 MB/sec throughput, and attach a Kinesis Data Firehose delivery stream that writes to the S3 bucket.
Publish the events to an Amazon SQS standard queue and invoke an AWS Lambda function that batches records and writes them to S3.
Deploy an Amazon MSK cluster and configure Kafka Connect to continuously sink the data to S3.
Amazon Kinesis Data Streams can retain records for 24 hours by default, allowing the team to re-read or replay any portion of the stream if a downstream job fails. Attaching a Kinesis Data Firehose delivery stream to the same data stream provides fully managed, low-touch delivery of the records to Amazon S3. A Kinesis Data Stream shard supports 1 MB/sec of write throughput, so five shards are needed to handle the 5 MB/sec ingestion rate. Sending data straight to Firehose would remove the ability to replay because Firehose does not store data after it is delivered. Using Amazon SQS with Lambda or deploying Amazon MSK would satisfy replay requirements but introduces higher operational overhead and, in the case of MSK, higher cost compared with a serverless Kinesis approach.
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AWS Certified Data Engineer Associate DEA-C01
Data Ingestion and Transformation
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