SAA-C03 · Question #708
A company needs a solution to ingest streaming sensor data from 100,000 devices, transform the data in near real time, and load the data into Amazon S3 for analysis. The solution must be fully…
The correct answer is A. Use Amazon Kinesis Data Streams to ingest the data. Use Amazon Managed Service for Apache. Amazon Kinesis Data Streams provides fully managed, scalable ingestion with very low latency suitable for high-volume streaming data. Amazon Managed Service for Apache Flink performs near-real-time (streaming) transformations continuously as data arrives. Delivering the…
Question
A company needs a solution to ingest streaming sensor data from 100,000 devices, transform the data in near real time, and load the data into Amazon S3 for analysis. The solution must be fully managed, scalable, and maintain sub-second ingestion latency. Which solution will meet these requirements in the MOST operationally efficient way?
Options
- AUse Amazon Kinesis Data Streams to ingest the data. Use Amazon Managed Service for Apache
- BUse Amazon Simple Queue Service (Amazon SQS) standard queues to collect the sensor data.
- CDeploy a fleet of Amazon EC2 instances that run Apache Kafka to ingest the data. Run Apache
- DImplement Amazon EventBridge to capture all sensor data. Use AWS Batch to run containerized
How the community answered
(26 responses)- A69% (18)
- B19% (5)
- C4% (1)
- D8% (2)
Explanation
Amazon Kinesis Data Streams provides fully managed, scalable ingestion with very low latency suitable for high-volume streaming data. Amazon Managed Service for Apache Flink performs near-real-time (streaming) transformations continuously as data arrives. Delivering the processed stream to Amazon S3 through an Amazon Data Firehose stream provides a fully managed, operationally efficient path to land the transformed data in S3 for analytics while maintaining sub- second ingestion latency.
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