Previous edition: published as by Neha Narkhede, Gwen Shapira and Todd Palino. Beijing: O'Reilly, 2017. Includes index.
Contents:
Meet Kafka -- Installing Kafka -- Kafka producers: writing messages to Kafka -- Kafka consumers: reading data from Kafka -- Managing Apache Kafka programmatically -- Kafka internals -- Reliable data delivery -- Exactly-once semantics -- Building data pipelines -- Cross-cluster data mirroring -- Securing Kafka -- Administering Kafka -- Monitoring Kafka -- Stream processing.
Summary:
"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." -- Provided by publisher.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.