Kafka: The Definitive Guide, 2nd Edition
Real-Time Data and Stream Processing at Scale
Book Details
| Authors | Gwen Shapira, Todd Palino, Rajini Sivaram, Krit Petty |
| Publisher | O'Reilly Media |
| Published | 2021 |
| Edition | 2nd |
| Paperback | 486 pages |
| Language | English |
| ISBN-13 | 9781492043089 |
| ISBN-10 | 1492043087 |
| License | Compliments of Confluent |
Book Description
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 streaming platform will learn how to handle data in motion. Additional chapters cover Kafka's AdminClient API, transactions, new security features, and tooling changes.
Engineers from Confluent and LinkedIn responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.
You'll examine:
- Best practices for deploying and configuring Kafka
- Kafka producers and consumers for writing and reading messages
- Patterns and use-case requirements to ensure reliable data delivery
- Best practices for building data pipelines and applications with Kafka
- How to perform monitoring, tuning, and maintenance tasks with Kafka in production
- The most critical metrics among Kafka's operational measurements
- Kafka's delivery capabilities for stream processing systems
This book is published as open-access, which means it is freely available to read, download, and share without restrictions.
If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.
Download and Read Links
Share this Book
[localhost]# find . -name "*Similar_Books*"
Jenkins: The Definitive Guide
Streamline software development with Jenkins, the popular Java-based open source tool that has revolutionized the way teams think about Continuous Integration (CI). This complete guide shows you how to automate your build, integration, release, and deployment processes with Jenkins - and demonstrates how CI can save you time, money, and many headac
Delta Lake: The Definitive Guide
Ready to simplify the process of building data lakehouses and data pipelines at scale? In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Pra
Presto: The Definitive Guide
Perform fast interactive analytics against different data sources using the Presto high-performance, distributed SQL query engine. With this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's Hive, Cassandra, a relational database, or a proprietary data store. Analysts, software engineers, and production eng
The SysAdmin Handbook
Over the past two years, Simple-Talk has published articles on a variety of SysAdmin topics, from Exchange to Virtualization, and including everything from Powershell to Unified Messaging. We have brought the best of these articles together to form The SysAdmin Handbook. With over fifty articles packed into this book, it will be an essential refere
CouchDB: The Definitive Guide
Three of CouchDB's creators show you how to use this document-oriented database as a standalone application framework or with high-volume, distributed applications. With its simple model for storing, processing, and accessing data, CouchDB is ideal for web applications that handle huge amounts of loosely structured data. That alone would stretch th
Unlock Data Agility with Composable Data Architecture
Are your data systems slowing down your AI initiatives? The potential of AI to revolutionize business is undeniable, but many organizations struggle to bridge the gap between ambitious ideas and real-world results. The cause? Traditional data architectures remain too rigid and siloed to support today's dynamic, data-intensive demands. If you're a d