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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
Biografía del autor
Neha Narkhede is Cofounder and Head of Engineering at Confluent, a company backing the popular Apache Kafka messaging system. Prior to founding Confluent, Neha led streams infrastructure at LinkedIn where she was responsible for LinkedIn s petabyte scale streaming infrastructure built on top of Apache Kafka and Apache Samza. Neha specializes in building and scaling large distributed systems and is one of the initial authors of Apache Kafka. In the past she has worked on search within the database at Oracle and holds a Masters in Computer Science from Georgia Tech.Gwen is a Software Engineer at Cloudera, working on data ingest and focusing on Apache Kafka. She is a frequent contributor to the Apache Kafka project, she has contributed Kafka integration to Apache Flume, and is a committer on Apache Sqoop.Gwen has 15 years of experience working with customers to design scalable data architectures.Formerly a solution architect at Cloudera, senior consultant at Pythian, Oracle ACE Director, and board member at NoCOUG. Gwen is a frequent speaker at industry conferences andcontributes to multiple industry blogs including O Reilly Radar and Ingest.Tips.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 industryrunning 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."
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- VerlagO'Reilly Media, Inc, USA
- Erscheinungsdatum2017
- ISBN 10 1491936169
- ISBN 13 9781491936160
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten297
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Kafka: the Definitive Guide : Real-Time Data and Stream Processing at Scale
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O'Reilly Media, Incorporated, 2017
ISBN 10: 1491936169
ISBN 13: 9781491936160
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