DEA-C01 · Question #298
A company needs to transform IoT sensor data in near real time before the company stores the data in an Amazon S3 bucket. The data is available from a data stream in Amazon Kinesis Data Streams. The…
The correct answer is B. Configure an application in Amazon Managed Service for Apache Flink to process the data. Amazon Managed Service for Apache Flink is purpose-built for near-real-time stream processing on Kinesis Data Streams and supports complex, stateful transformations with managed scaling, state management, and checkpointing, resulting in the lowest operational overhead for this…
Question
A company needs to transform IoT sensor data in near real time before the company stores the data in an Amazon S3 bucket. The data is available from a data stream in Amazon Kinesis Data Streams. The company needs to apply complex and stateful transformations to the data before the company stores the data. Which solution will meet these requirements with the LEAST operational overhead?
Options
- ASchedule AWS Glue ETL jobs to process the data stream.
- BConfigure an application in Amazon Managed Service for Apache Flink to process the data
- CConfigure an AWS Lambda function to process the data stream.
- DSchedule Apache Spark jobs on an Amazon EMR cluster to process the data stream.
How the community answered
(35 responses)- A6% (2)
- B77% (27)
- C14% (5)
- D3% (1)
Explanation
Amazon Managed Service for Apache Flink is purpose-built for near-real-time stream processing on Kinesis Data Streams and supports complex, stateful transformations with managed scaling, state management, and checkpointing, resulting in the lowest operational overhead for this use
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