Chapter 1, Introduction to Messaging System, introduces concepts of messaging systems. It covers an overview of messaging systems and their enterprise needs. It further emphasizes the different ways of using messaging systems such as point to point or publish/subscribe. It introduces AMQP as well.
Chapter 2, Introducing Kafka - The Distributed Messaging Platform, introduces distributed messaging platforms such as Kafka. It covers the Kafka architecture and touches upon its internal component. It further explores the roles and importance of each Kafka components and how they contribute towards low latency, reliability, and the scalability of Kafka Message Systems.
Chapter 3, Deep Dive into Kafka Producers, is about how to publish messages to Kafka Systems. This further covers Kafka Producer APIs and their usage. It showcases examples of using Kafka Producer APIs with Java and Scala programming languages. It takes a deep dive into Producer message flows and some common patterns for producing messages to Kafka Topics. It walks through some performance optimization techniques for Kafka Producers.
Chapter 4, Deep Dive into Kafka Consumers, is about how to consume messages from Kafka Systems. This also covers Kafka Consumer APIs and their usage. It showcases examples of using Kafka Consumer APIs with the Java and Scala programming languages. It takes a deep dive into Consumer message flows and some common patterns for consuming messages from Kafka Topics. It walks through some performance optimization techniques for Kafka Consumers.
Chapter 5, Building Spark Streaming Applications with Kafka, is about how to integrate Kafka with the popular distributed processing engine, Apache Spark. This also provides a brief overview about Apache Kafka, the different approaches for integrating Kafka with Spark, and their advantages and disadvantages. It showcases examples in Java as well as in Scala with use cases.
Chapter 6, Building Storm Applications with Kafka, is about how to integrate Kafka with the popular real-time processing engine Apache Storm. This also covers a brief overview of Apache Storm and Apache Heron. It showcases examples of different approaches of event processing using Apache Storm and Kafka, including guaranteed event processing.
Chapter 7, Using Kafka with Confluent Platform, is about the emerging streaming platform Confluent that enables you to use Kafka effectively with many other added functionalities. It showcases many examples for the topics covered in the chapter.
Chapter 8, Building ETL Pipelines Using Kafka, introduces Kafka Connect, a common component, which for building ETL pipelines involving Kafka. It emphasizes how to use Kafka Connect in ETL pipelines and discusses some in-depth technical concepts surrounding it.
Chapter 9, Building Streaming Applications Using Kafka Streams, is about how to build streaming applications using Kafka Stream, which is an integral part of the Kafka 0.10 release. This also covers building fast, reliable streaming applications using Kafka Stream, with examples.
Chapter 10, Kafka Cluster Deployment, focuses on Kafka cluster deployment on enterprise-grade production systems. It covers in depth, Kafka clusters such as how to do capacity planning, how to manager single/multi cluster deployments, and so on. It also covers how to manage Kafka in multi-tenant environments. It further walks you through the various steps involved in Kafka data migrations.
Chapter 11, Using Kafka in Big Data Applications, walks through some of the aspects of using Kafka in big data applications. This covers how to manage high volumes in Kafka, how to ensure guaranteed message delivery, the best ways to handle failures without any data loss, and some governance principles that can be applied while using Kafka in big data pipelines.
Chapter 12, Securing Kafka, is about securing your Kafka cluster. It covers authentication and authorization mechanisms along with examples.
Chapter 13, Streaming Applications Design Considerations, is about different design considerations for building a streaming application. It walks you through aspects such as parallelism, memory tuning, and so on. It provides comprehensive coverage of the different paradigms for designing a streaming application.
