In Kafka in Action you will learn:

Understanding Apache Kafka concepts
Setting up and executing basic ETL tasks using Kafka Connect
Using Kafka as part of a large data project team
Performing administrative tasks
Producing and consuming event streams
Working with Kafka from Java applications
Implementing Kafka as a message queue

Kafka in Action is a fast-paced introduction to every aspect of working with Apache Kafka. Starting with an overview of Kafka's core concepts, you'll immediately learn how to set up and execute basic data movement tasks and how to produce and consume streams of events. Advancing quickly, you’ll soon be ready to use Kafka in your day-to-day workflow, and start digging into even more advanced Kafka topics.

About the technology
Think of Apache Kafka as a high performance software bus that facilitates event streaming, logging, analytics, and other data pipeline tasks. With Kafka, you can easily build features like operational data monitoring and large-scale event processing into both large and small-scale applications.

About the book
Kafka in Action introduces the core features of Kafka, along with relevant examples of how to use it in real applications. In it, you’ll explore the most common use cases such as logging and managing streaming data. When you’re done, you’ll be ready to handle both basic developer- and admin-based tasks in a Kafka-focused team.

What's inside

Kafka as an event streaming platform
Kafka producers and consumers from Java applications
Kafka as part of a large data project

About the reader
For intermediate Java developers or data engineers. No prior knowledge of Kafka required.

About the Author

Dylan Scott is a software developer in the insurance industry.

Viktor Gamov is a Kafka-focused developer advocate. At Confluent,

Dave Klein helps developers, teams, and enterprises harness the power of event streaming with Apache Kafka.

Table of Contents

PART 1 GETTING STARTED
1 Introduction to Kafka
2 Getting to know Kafka

PART 2 APPLYING KAFK
3 Designing a Kafka project
4 Producers: Sourcing data
5 Consumers: Unlocking data
6 Brokers
7 Topics and partitions
8 Kafka storage
9 Management: Tools and logging

PART 3 GOING FURTHER
10 Protecting Kafka
11 Schema registry
12 Stream processing with Kafka Streams and ksqlDB

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