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Developing Stream Processing Applications with AWS Kinesis

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Duration

4h 11m

level

Intermediate

Course Creator

Ivan Mushketyk

Last Updated

13-May-20

AWS Kinesis is a powerful, real-time, elastic, reliable service for stream processing. This course will teach you how to build modern stream processing applications using AWS Kinesis, stream processing services, and Big Data frameworks.

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The landscape of the Big Data field is changing. Previously, you could go away with processing incoming data for hours or even days. Now you need to do it in minutes or even seconds. These challenges require new solutions, new architectures, and new tools. AWS Kinesis is a service for stream processing that allows building applications that were impossible to create before. In the course, Developing Stream Processing Applications with AWS Kinesis, you’ll learn the ins and outs of AWS Kinesis. First, you’ll discover how it works, how to scale it up and down, and how to write applications using it. Next, you’ll learn how to use a variety of tools to work with it, such as Kinesis Client Library, Kinesis Connector Library, Apache Flink, and AWS Lambda. Finally, you’ll explore how to use more high-level Kinesis products such as Kinesis Firehose and how to write streaming applications using SQL queries with Kinesis Analytics. When you are finished with this course, you’ll have an in-depth knowledge of AWS Kinesis that will help you to build your streaming applications.
Author Name: Ivan Mushketyk
Author Description:
Ivan is a Principal Software Engineer and a Tech Lead who is passionate about Big Data and Cloud Computing. He has worked for numerous big IT companies including Samsung and Amazon Web Services. He is an Open Source enthusiast and has contributed to a number of projects including Gatling and Apache Flink. When he is not writing code or working on a new course, he is probably writing another technical article for his blog.

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Developing Stream Processing Applications with AWS Kinesis
Developing Stream Processing Applications with AWS Kinesis
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