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Building Data Streaming Applications with Apache Kafka

Building Data Streaming Applications with Apache Kafka

By : Singh, Kumar
3.8 (4)
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Building Data Streaming Applications with Apache Kafka

Building Data Streaming Applications with Apache Kafka

3.8 (4)
By: Singh, Kumar

Overview of this book

Apache Kafka is a popular distributed streaming platform that acts as a messaging queue or an enterprise messaging system. It lets you publish and subscribe to a stream of records, and process them in a fault-tolerant way as they occur. This book is a comprehensive guide to designing and architecting enterprise-grade streaming applications using Apache Kafka and other big data tools. It includes best practices for building such applications, and tackles some common challenges such as how to use Kafka efficiently and handle high data volumes with ease. This book first takes you through understanding the type messaging system and then provides a thorough introduction to Apache Kafka and its internal details. The second part of the book takes you through designing streaming application using various frameworks and tools such as Apache Spark, Apache Storm, and more. Once you grasp the basics, we will take you through more advanced concepts in Apache Kafka such as capacity planning and security. By the end of this book, you will have all the information you need to be comfortable with using Apache Kafka, and to design efficient streaming data applications with it.
Table of Contents (14 chapters)
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Kafka Cluster Deployment

In the previous chapters, we talked about the different use cases associated with Apache Kafka. We shed light on different technologies and frameworks associated with the Kafka messaging system. However, putting Kafka to production use requires additional tasks and knowledge. Firstly, you must have a very thorough understanding of how the Kafka cluster works. Later on, you must determine the hardware required for the Kafka cluster by performing adequate capacity planning. You need to understand Kafka deployment patterns and how to perform day-to-day Kafka administrating activities. In this chapter, we will cover the following topics:

  • Kafka cluster internals
  • Capacity planning
  • Single-cluster deployment
  • Multi-cluster deployment
  • Decommissioning brokers
  • Data migration

In a nutshell, this chapter focuses on Kafka cluster deployment on enterprise grade production...

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