Mastering Apache Kafka

There is a vast gap between running the Apache Kafka quickstart and running Kafka in production. This book closes that gap.

Mastering Apache Kafka takes you from the original log abstraction invented at LinkedIn in 2010 all the way to designing, securing, tuning, and operating real-time streaming platforms at scale. Instead of stopping at toy examples, it gives you practical, production-grade guidance shaped by how the world’s leading engineering teams actually use Kafka.

Every chapter opens with a documented, real-world scenario from companies like Netflix, Uber, Airbnb, LinkedIn, Goldman Sachs, and Shopify. You see the problem they faced, why event streaming solved it, and how to apply the same thinking to your own systems. Every statistic is backed by its source and publication date, so you can trust what you read.

The book is fully current with the modern Kafka platform, including KRaft-based metadata, the next-generation consumer group protocol, share groups for queue-style workloads, and tiered storage, up to the Kafka 4.4.0 release.

Inside, you will learn how to:

• Understand brokers, topics, partitions, replication, offsets, and delivery semantics at a deep level
• Spin up a local cluster with Docker and write producers and consumers in both Java and Python
• Manage schemas with Avro, Protobuf, and Schema Registry
• Integrate external systems with Kafka Connect
• Build stream processing applications with Kafka Streams and ksqlDB
• Secure your clusters with TLS, SASL, and ACLs
• Monitor, measure, and tune performance using real metrics
• Deploy on Kubernetes and managed cloud services
• Recognize and fix the anti-patterns that break real clusters

Each chapter builds on the last toward a complete capstone project: a real-time order processing and fraud detection pipeline you assemble piece by piece.

Written for software engineers, data engineers, and solution architects, this is the guide for anyone ready to move from beginner to production-ready Kafka expertise.