Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
Narkhede, Neha; Shapira, Gwen; Palino, Todd
Language: English
Published by O'Reilly Media, 2017
- Softcover
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- Title
- Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
- Author
- Narkhede, Neha; Shapira, Gwen; Palino, Todd
- Publisher
- O'Reilly Media
- Publication year
- 2017
- Condition
- Good
- Dust jacket
- No Jacket
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1491936169
- ISBN 13
- 9781491936160
- Item weight
- 1.22 pounds
Every enterprise application creates data, whether it’s 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 you’re an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds.
Engineers from Confluent and LinkedIn who are 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.
- Understand publish-subscribe messaging and how it fits in the big data ecosystem.
- Explore Kafka producers and consumers for writing and reading messages
- Understand Kafka patterns and use-case requirements to ensure reliable data delivery
- Get best practices for building data pipelines and applications with Kafka
- Manage Kafka in production, and learn to perform monitoring, tuning, and maintenance tasks
- Learn the most critical metrics among Kafka’s operational measurements
- Explore how Kafka’s stream delivery capabilities make it a perfect source for stream processing systems
"Synopsis" may belong to another edition of this title.
About the Author
Gwen Shapira is a system architect at Confluent helping customers achieve success with their Apache Kafka implementation. She has 15 years of experience working with code and customers to build scalable data architectures, integrating relational and big data technologies. She currently specializes in building real-time reliable data processing pipelines using Apache Kafka. Gwen is an Oracle Ace Director, an author of "Hadoop Application Architectures", and a frequent presenter at data driven conferences. Gwen is also a committer on the Apache Kafka and Apache Sqoop projects.
Todd is a Staff Site Reliability Engineer at LinkedIn, tasked with keeping the largest deployment of Apache Kafka, Zookeeper, and Samza fed and watered. He is responsible for architecture, day-to-day operations, and tools development, including the creation of an advanced monitoring and notification system. Todd is the developer of the open source project Burrow, a Kafka consumer monitoring tool, and can be found sharing his experience on Apache Kafka at industry conferences and tech talks. Todd has spent over 20 years in the technology industry running infrastructure services, most recently as a Systems Engineer at Verisign, developing service management automation for DNS, networking, and hardware management, as well as managing hardware and software standards across the company.
"About the title" may belong to another edition of this title.
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