Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka streami
Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
β Scribed by Neha Narkhede, Gwen Shapira, Todd Palino
- Publisher
- OβReilly Media
- Year
- July 2017
- Tongue
- English
- Leaves
- 322
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Learn how to take full advantage of Apache Kafka, the distributed, publish-subscribe queue for handling real-time data feeds. With this comprehensive book, you'll understand how Kafka works and how it's designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino show you how to deploy production Kafka clusters; secure, tune, and monitor them; write rock-solid applications that use Kafka; and build scalable stream-processing applications.
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Every enterprise application creates data, whether itβs log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If youβre an application architect, developer, or production engineer new to Apache Kaf
<p><span>Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafk
<div><p>Every enterprise application creates data, whether it consists of log messages, metrics, user activity, or outgoing messages. Moving all this data is just as important as the data itself. With this updated edition, application architects, developers, and production engineers new to the Kafka
Table of Contents; Foreword; Preface; Who Should Read This Book; Conventions Used in This Book; Using Code Examples; O'Reilly Safari; How to Contact Us; Acknowledgments; Chapter 1. Meet Kafka; Publish/Subscribe Messaging; How It Starts; Individual Queue Systems; Enter Kafka; Messages and Batches; Sc