Kafka: The Definitive Guide

Gwen Shapira works as a system architect at Confluent, assisting customers with their Apache Kafka implementation. She has more than 15 years of experience working with code and clients to create scalable data architectures that integrate relational and big data technologies.

Todd works as a Staff Site Reliability Engineer at LinkedIn, where he is in charge of feeding and watering the company's largest deployment of Apache Kafka, Zookeeper, and Samza. He is in charge of architecture, day-to-day operations, and tool development, as well as the development of an advanced monitoring and alerting system.

Rajini Sivaram works at Confluent as a Software Engineer, creating and developing security features for Kafka. She is a member of the Apache Kafka Program Management Committee and an Apache Kafka Committer.

Krit Petty works at LinkedIn as the Site Reliability Engineering Manager for Kafka. Krit holds a Master's Degree in Computer Science and has previously worked as a Linux system administrator and as a Software Engineer in the oil and gas business, designing software for high-performance computing projects.

Data is generated by every enterprise program, whether it is log messages, metrics, user activity, or outgoing communications. Moving all of this data is as critical as the data itself. This updated edition of Kafka: The Definitive Guide will teach application architects, developers, and production engineers who are new to the Kafka streaming platform how to manage data in motion. Other chapters address the AdminClient API of Kafka, transactions, new security capabilities, and tooling updates.

Engineers from Confluent and LinkedIn responsible for building Kafka describe how to use this platform to install production Kafka clusters, construct dependable event-driven microservices, and build scalable stream processing applications. You'll discover Kafka's design principles, reliability guarantees, essential APIs, and architecture specifics, such as the replication protocol, the controller, and the storage layer, through extensive examples.

You will investigate:

• Best practices for Kafka deployment and configuration
• Kafka producers and consumers for message writing and reading
• Reliable data delivery requires patterns and use-case criteria.
• Best practices for designing Kafka data pipelines and applications
• How to use Kafka in production for monitoring, tweaking, and maintenance.
• The most important operational measurements in Kafka
• The delivery capabilities of Kafka for stream processing systems

Author: Gwen Shapira, Rajini Sivaram, Krit Petty and Todd Palino

Link to buy: https://www.amazon.com/Kafka-Definitive-Real-Time-Stream-Processing/dp/1492043087/

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