Developing Stream Processing Applications with AWS Kinesis
AWS Kinesis is a powerful, real-time, elastic, reliable service for stream processing. This course will teach you how to build stream processing applications using AWS Kinesis, stream processing services, and Big Data frameworks.
What you'll learn
The landscape of the Big Data field is changing. Previously, you could get 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.
In Developing Stream Processing Applications with AWS Kinesis, you will learn the ins and outs of AWS Kinesis. First, you will learn how it works, how to scale it up and down, and how to write applications with it. Next, you will explore 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 will discover 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 will have an in-depth knowledge of AWS Kinesis that will help you to build your streaming applications.
Table of contents
- Introduction 5m
- History of Kinesis 3m
- Kinesis Building Blocks 6m
- Kinesis API 3m
- Setting up AWS Environment 2m
- Accessing Kinesis Streams 6m
- Scaling Model 3m
- Scaling Kinesis Stream 6m
- Kinesis Limitations 4m
- Comparing to Other Technologies 3m
- Server-side Encryption 2m
- Monitoring Kinesis Stream 3m
- Summary 2m
- Introduction 2m
- Reading Data from Twitter 5m
- Kinesis Producer Library 7m
- Implementing Kinesis Producer 4m
- Kinesis Client Library 5m
- Implementing Simple Kinesis Consumer 6m
- Checkpoints in KCL 2m
- Implementing Fault Tollerant Kinesis Consumer 3m
- Tweets Analytics 3m
- Implementing Tweets Analytics 7m
- Handling Resharding 3m
- Summary 4m
About the author
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.