
Explanation:
Option B is the most suitable choice for building a data pipeline that ingests real-time streaming data from IoT devices and processes it using machine learning models. Amazon Kinesis Data Firehose is a fully managed service that can ingest real-time streaming data from IoT devices and deliver it to various AWS services. Amazon SageMaker is a fully managed service that provides end-to-end machine learning capabilities, including building, training, and deploying machine learning models. By using Amazon Kinesis Data Firehose and Amazon SageMaker together, you can set up a data pipeline that ingests real-time streaming data, processes it using machine learning models, and takes the necessary actions based on the results.
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You are tasked with designing a data pipeline that ingests real-time streaming data from IoT devices and processes it using machine learning models. Which AWS services would you use to build this pipeline, and how would you set it up?
A
Amazon Kinesis and AWS Lambda
B
Amazon Kinesis Data Firehose and Amazon SageMaker
C
AWS Glue and Amazon SageMaker
D
AWS Step Functions and Amazon S3