Kafka: The Definitive Guide: Real-Time Data and Stream Processing at Scale
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.
다른 사람들의 의견 - 서평 쓰기
Chapter 1 Meet Kafka
Chapter 2 Installing Kafka
Writing Messages to Kafka
Reading Data from Kafka
Chapter 5 Kafka Internals
Chapter 6 Reliable Data Delivery
Chapter 7 Building Data Pipelines
Chapter 8 CrossCluster Data Mirroring