AWS Certified Data Engineer Associate DEA-C01 Practice Question
A retail company ingests 50,000 clickstream events per second into an on-premises Apache Kafka cluster. The team wants to migrate the workload to AWS to eliminate patching and node failures while keeping existing Kafka producer and consumer code, retaining data for 7 days, and minimizing ongoing operational cost. Which approach meets these requirements?
Create an Amazon Kinesis Data Stream with enough shards, enable 7-day extended retention, and migrate producers to use the Kinesis Producer Library.
Write events directly to Amazon DynamoDB using Kinesis Data Streams for DynamoDB and enable DynamoDB Time to Live (TTL) set to 7 days.
Provision a multi-AZ Amazon MSK cluster with the required number of brokers and set the topic retention to 7 days.
Send events to an Amazon SQS FIFO queue, trigger AWS Lambda for processing, and archive messages in Amazon S3 after 7 days.
Amazon MSK provides a fully managed, highly available Apache Kafka environment. Existing Kafka clients can connect without code changes, and topic retention can be configured to 7 days. AWS handles broker provisioning, patching, and recovery, reducing operational overhead and cost. Kinesis Data Streams would require rewriting applications to the Kinesis APIs. SQS FIFO and DynamoDB are not suitable for high-throughput Kafka workloads and would also require substantial refactoring.
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AWS Certified Data Engineer Associate DEA-C01
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