Apache Kafka In Action
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Apache Kafka in Action
Author: Anatoly Zelenin
language: en
Publisher: Simon and Schuster
Release Date: 2025-06-24
Apache Kafka, start to finish. Apache Kafka in Action: From basics to production guides you through the concepts and skills you’ll need to deploy and administer Kafka for data pipelines, event-driven applications, and other systems that process data streams from multiple sources. Authors Anatoly Zelenin and Alexander Kropp have spent years using Kafka in real-world production environments. In this guide, they reveal their hard-won expert insights to help you avoid common Kafka pitfalls and challenges. Inside Apache Kafka in Action you’ll discover: • Apache Kafka from the ground up • Achieving reliability and performance • Troubleshooting Kafka systems • Operations, governance, and monitoring • Kafka use cases, patterns, and anti-patterns Clear, concise, and practical, Apache Kafka in Action is written for IT operators, software engineers, and IT architects working with Kafka every day. Chapter by chapter, it guides you through the skills you need to deliver and maintain reliable and fault-tolerant data-driven applications. Foreword by Adam Bellemare. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Apache Kafka is the gold standard streaming data platform for real-time analytics, event sourcing, and stream processing. Acting as a central hub for distributed data, it enables seamless flow between producers and consumers via a publish-subscribe model. Kafka easily handles millions of events per second, and its rock-solid design ensures high fault tolerance and smooth scalability. About the book Apache Kafka in Action is a practical guide for IT professionals who are integrating Kafka into data-intensive applications and infrastructures. The book covers everything from Kafka fundamentals to advanced operations, with interesting visuals and real-world examples. Readers will learn to set up Kafka clusters, produce and consume messages, handle real-time streaming, and integrate Kafka into enterprise systems. This easy-to-follow book emphasizes building reliable Kafka applications and taking advantage of its distributed architecture for scalability and resilience. What's inside • Master Kafka’s distributed streaming capabilities • Implement real-time data solutions • Integrate Kafka into enterprise environments • Build and manage Kafka applications • Achieve fault tolerance and scalability About the reader For IT operators, software architects and developers. No experience with Kafka required. About the author Anatoly Zelenin is a Kafka expert known for workshops across Europe, especially in banking and manufacturing. Alexander Kropp specializes in Kafka and Kubernetes, contributing to cloud platform design and monitoring. Table of Contents Part 1 1 Introduction to Apache Kafka 2 First steps with Kafka Part 2 3 Exploring Kafka topics and messages 4 Kafka as a distributed log 5 Reliability 6 Performance Part 3 7 Cluster management 8 Producing and persisting messages 9 Consuming messages 10 Cleaning up messages Part 4 11 Integrating external systems with Kafka Connect 12 Stream processing 13 Governance 14 Kafka reference architecture 15 Kafka monitoring and alerting16 Disaster management 17 Comparison with other technologies 18 Kafka’s role in modern enterprise architectures Appendixes A Setting up a Kafka test environment B Monitoring setup
Event Streams in Action
Author: Valentin Crettaz
language: en
Publisher: Simon and Schuster
Release Date: 2019-05-10
Summary Event Streams in Action is a foundational book introducing the ULP paradigm and presenting techniques to use it effectively in data-rich environments. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many high-profile applications, like LinkedIn and Netflix, deliver nimble, responsive performance by reacting to user and system events as they occur. In large-scale systems, this requires efficiently monitoring, managing, and reacting to multiple event streams. Tools like Kafka, along with innovative patterns like unified log processing, help create a coherent data processing architecture for event-based applications. About the Book Event Streams in Action teaches you techniques for aggregating, storing, and processing event streams using the unified log processing pattern. In this hands-on guide, you'll discover important application designs like the lambda architecture, stream aggregation, and event reprocessing. You'll also explore scaling, resiliency, advanced stream patterns, and much more! By the time you're finished, you'll be designing large-scale data-driven applications that are easier to build, deploy, and maintain. What's inside Validating and monitoring event streams Event analytics Methods for event modeling Examples using Apache Kafka and Amazon Kinesis About the Reader For readers with experience coding in Java, Scala, or Python. About the Author Alexander Dean developed Snowplow, an open source event processing and analytics platform. Valentin Crettaz is an independent IT consultant with 25 years of experience. Table of Contents PART 1 - EVENT STREAMS AND UNIFIED LOGS Introducing event streams The unified log 24 Event stream processing with Apache Kafka Event stream processing with Amazon Kinesis Stateful stream processing PART 2- DATA ENGINEERING WITH STREAMS Schemas Archiving events Railway-oriented processing Commands PART 3 - EVENT ANALYTICS Analytics-on-read Analytics-on-write
Kafka: The Definitive Guide
Author: Neha Narkhede
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2017-08-31
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