You need to use machine learning to produce real-time analysis of streaming data from IoT devices out in the field. These devices monitor oil well rigs for malfunction. Due to the safety and security nature of these IoT events, the events must be analyzed by your safety engineers in real-time. You also have an audit requirement to retain your IoT device events for 7 days since you cannot fail to process any of the events. Which approach would give you the best solution for processing your streaming data?

Answer options:

A.Use Amazon Kinesis Data Streams and its Kinesis Producer Library to pass your events from your producers to your Kinesis stream.
B.Use Amazon Kinesis Data Streams and its Kinesis API PutRecords call to pass your events from your producers to your Kinesis stream.
C.Use Amazon Kinesis Data Streams and its Kinesis Client Library to pass your events from your producers to your Kinesis stream.
D.Use Amazon Kinesis Data Firehose to pass your events directly to your S3 bucket where you store your machine learning data.

Answer: B
Option A is incorrect. The Amazon Kinesis Data Streams Producer Library is not meant to be used for real-time processing of event data since, according to the AWS developer documentation, “it can incur an additional processing delay of up to RecordMaxBufferedTime within the library”. Therefore, it is not the best solution for a real-time analytics solution. (See the AWS developer documentation titled Developing Producers Using the Amazon Kinesis Producer Library)
Option B is correct. The Amazon Kinesis Data Streams API PutRecords call is the best choice for processing in real-time since it sends its data synchronously and does not have the processing delay of the Producer Library. Therefore, it is better suited to real-time applications. (See the AWS developer documentation titled Developing Producers Using the Amazon Kinesis Data Streams API with the AWS SDK for Java)
Option C is incorrect. The Amazon Kinesis Data Streams Client Library interacts with the Kinesis Producer Library to process its event data. Therefore, you’ll have the same processing delay problem with this option. (See the AWS developer documentation titled Developing Consumers Using the Kinesis Client Library 1.x)
Option D is incorrect. The Amazon Kinesis Data Firehose service directly streams your event data to your S3 bucket for use in your real-time analytics model. However, Amazon Kinesis Data Firehose retries to send your data for a maximum of 24 hours, but you have a 7-day retention requirement. (See the Amazon Kinesis Data Firehose FAQs)
Reference:
Please see the Amazon Kinesis Data Streams documentation.