MLS-C01 Question 32
Single answerYour company is building a real-time analytics platform to process and analyze streaming data from IoT devices deployed across multiple locations. The platform needs to ingest high-throughput data, process it in near real-time, and store the results in Amazon S3 for further analysis. Which service configuration would best meet these requirements?
- A
Use Amazon Kinesis Data Streams to ingest the streaming data, Kinesis Data Analytics to process the data, and Kinesis Data Firehose to deliver the results to Amazon S3.
- B
Use Amazon SQS to ingest the streaming data, AWS Lambda to process the data, and Amazon SNS to deliver the results to Amazon S3.
- C
Use Amazon Kinesis Data Streams to ingest the streaming data, AWS Lambda to process the data, and Amazon DynamoDB to store the results.
- D
Use Amazon Kinesis Data Firehose to ingest the streaming data, Kinesis Data Analytics to process the data, and Amazon Redshift to store the results.
Show answer and explanation
Correct answer: A
Explanation
Amazon Kinesis is purpose-built for real-time data streaming and processing. The combination of Kinesis Data Streams, Kinesis Data Analytics, and Kinesis Data Firehose is an optimal solution for ingesting, processing, and delivering streaming data to Amazon S3 for storage and further analytics. This configuration ensures scalability, low latency, and seamless integration with AWS services.
- A. Correct.
This is the correct configuration. Kinesis Data Streams is used for high-throughput data ingestion, Kinesis Data Analytics processes the data in real-time, and Kinesis Data Firehose reliably delivers the processed data to Amazon S3.
- B. Incorrect.
Amazon SQS is not designed for high-throughput streaming data ingestion, and Amazon SNS is not suitable for delivering data to Amazon S3.
- C. Incorrect.
While Kinesis Data Streams and AWS Lambda could be used together, DynamoDB is not the ideal choice for storing large volumes of processed analytics data intended for further analysis.
- D. Incorrect.
Kinesis Data Firehose cannot directly ingest high-throughput streaming data; it is designed for delivering data to destinations. Additionally, Amazon Redshift is not suitable for storing raw or intermediate processed data in real-time.