In this course, you will learn how you can use the Amazon Kinesis Data Analytics service to process streaming data using both the Apache Flink runtime and the SQL runtime. You will integrate your streaming applications with Kinesis Data Streams, Kinesis Data Firehose Delivery streams, and Amazon’s S3.
Kinesis Data Analytics is a service to transform and analyze streaming data in real-time with Apache Flink and SQL using serverless technologies. In this course, Conceptualizing the Processing Model for the AWS Kinesis Data Analytics Service, you will learn that Kinesis Data Analytics is part of the Kinesis streaming platform along with Kinesis Data Streams, Kinesis Data Firehose, and Kinesis Video streams. First, you will get introduced to the Kinesis Data Analytics service for processing and analyzing streams. You will explore the runtimes available that you can use to process your data which includes the Apache Flink runtime, the SQL runtime, and the Apache Beam runtime. You will then deploy a streaming application using the AWS command-line interface. This will involve setting up the correct roles and policies for your application to access the resources that it needs. Next, you will learn how you can deploy a Kinesis Analytics application using the web console. You will configure your streaming application to read from an enhanced fan-out consumer and write to Kinesis Firehose delivery streams. You will also explore using the Table API in Apache Flink to process streaming data. Finally, you will deploy and run Kinesis Data Analytics applications using the SQL runtime. The SQL runtime allows you to run interactive SQL queries to processing input streams, you will learn how to create and use in-application streams and understand the purpose of the stream pump. When you are finished with this course, you will have the skills and knowledge to create and deploy streaming applications on Kinesis Data Analytics and use connects to work with other AWS services as data sources and data sinks.
Kinesis Data Analytics is a service to transform and analyze streaming data in real-time with Apache Flink and SQL using serverless technologies. In this course, Conceptualizing the Processing Model for the AWS Kinesis Data Analytics Service, you will learn that Kinesis Data Analytics is part of the Kinesis streaming platform along with Kinesis Data Streams, Kinesis Data Firehose, and Kinesis Video streams. First, you will get introduced to the Kinesis Data Analytics service for processing and analyzing streams. You will explore the runtimes available that you can use to process your data which includes the Apache Flink runtime, the SQL runtime, and the Apache Beam runtime. You will then deploy a streaming application using the AWS command-line interface. This will involve setting up the correct roles and policies for your application to access the resources that it needs. Next, you will learn how you can deploy a Kinesis Analytics application using the web console. You will configure your streaming application to read from an enhanced fan-out consumer and write to Kinesis Firehose delivery streams. You will also explore using the Table API in Apache Flink to process streaming data. Finally, you will deploy and run Kinesis Data Analytics applications using the SQL runtime. The SQL runtime allows you to run interactive SQL queries to processing input streams, you will learn how to create and use in-application streams and understand the purpose of the stream pump. When you are finished with this course, you will have the skills and knowledge to create and deploy streaming applications on Kinesis Data Analytics and use connects to work with other AWS services as data sources and data sinks.
