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

Out of the massive research for an authoritative 1,500-page biography emerges this wunderkammer of 99 delightfully odd facts about Kafka In the course of compiling his highly acclaimed three-volume biography of Kafka, while foraying to libraries and archives from Prague to Israel, Reiner Stach made one astounding discovery after another: unexpected photographs, inconsistencies in handwritten texts, excerpts from letters, and testimonies from Kafka’s contemporaries that shed surprising light on his personality and his writing. Is that Kafka? presents the crystal granules of the real Kafka: he couldn’t lie, but he tried to cheat on his high-school exams; bitten by the fitness fad, he avidly followed the regime of a Danish exercise guru; he drew beautifully; he loved beer; he read biographies voraciously; he made the most beautiful presents, especially for children; odd things made him cry or made him furious; he adored slapstick. Every discovery by Stach turns on its head the stereotypical version of the tortured neurotic—and as each one chips away at the monolithic dark Kafka, the keynote, of all things, becomes laughter. For Is that Kafka? Stach has assembled 99 of his most exciting discoveries, culling the choicest, most entertaining bits, and adding his knowledge-able commentaries. Illustrated with dozens of previously unknown images, this volume is a singular literary pleasure.

Working with unbounded and fast-moving data streams has historically been difficult. But with Kafka Streams and ksqlDB, building stream processing applications is easy and fun. This practical guide shows data engineers how to use these tools to build highly scalable stream processing applications for moving, enriching, and transforming large amounts of data in real time. Mitch Seymour, data services engineer at Mailchimp, explains important stream processing concepts against a backdrop of several interesting business problems. You'll learn the strengths of both Kafka Streams and ksqlDB to help you choose the best tool for each unique stream processing project. Non-Java developers will find the ksqlDB path to be an especially gentle introduction to stream processing. Learn the basics of Kafka and the pub/sub communication pattern Build stateless and stateful stream processing applications using Kafka Streams and ksqlDB Perform advanced stateful operations, including windowed joins and aggregations Understand how stateful processing works under the hood Learn about ksqlDB's data integration features, powered by Kafka Connect Work with different types of collections in ksqlDB and perform push and pull queries Deploy your Kafka Streams and ksqlDB applications to production

This is not your ordinary short story collection. In his newest work, Daniel Chacón subverts expectation and bends the rules of reality to create stories that are intriguing, hilarious, and deeply rooted in Chicano culture. These stories explore the concept of a wall that reaches beyond our immediate thoughts of a towering physical structure. While Chacón aims to address the partition along the U.S.-Mexico border, he also uses these stories to work through the intangible walls that divide communities and individuals—particularly those who straddle multiple cultures in their daily lives. Set in El Paso and other Latinx-dominant urban spaces, Kafka in a Skirt is an immersive look into the myriad lives of the characters who inhabit these culturally diverse areas. Chacón masterfully weaves elements of the surreal and fantastic through a shining tapestry of fiction, creating moments of touching realism in contrast with scenes that are fascinatingly unfamiliar. Occasionally teasing the ghosts of Jorge Luis Borges and the Argentine poet Alejandra Pizarnik, this collection disregards boundaries and transports readers into a world merely parallel to our own. Kafka in a Skirt unravels the intricacies of culture, sexuality, love, and loneliness in a collection that shows the personal implications of barriers while remaining hopeful and bright.

The software architecture landscape has evolved dramatically over the past decade. Microservices have displaced monoliths. Data and applications are increasingly becoming distributed and decentralised. But composing disparate systems is a hard problem. More recently, software practitioners have been rapidly converging on event-driven architecture as a sustainable way of dealing with complexity - integrating systems without increasing their coupling.In Effective Kafka, Emil Koutanov explores the fundamentals of Event-Driven Architecture - using Apache Kafka - the world's most popular and supported open-source event streaming platform.You'll learn: - The fundamentals of event-driven architecture and event streaming platforms- The background and rationale behind Apache Kafka, its numerous potential uses and applications- The architecture and core concepts - the underlying software components, partitioning and parallelism, load-balancing, record ordering and consistency modes- Installation of Kafka and related tooling - using standalone deployments, clusters, and containerised deployments with Docker- Using CLI tools to interact with and administer Kafka classes, as well as publishing data and browsing topics- Using third-party web-based tools for monitoring a cluster and gaining insights into the event streams- Building stream processing applications in Java 11 using off-the-shelf client libraries- Patterns and best-practice for organising the application architecture, with emphasis on maintainability and testability of the resulting code- The numerous gotchas that lurk in Kafka's client and broker configuration, and how to counter them- Theoretical background on distributed and concurrent computing, exploring factors affecting their liveness and safety- Best-practices for running multi-tenanted clusters across diverse engineering teams, how teams collaborate to build complex systems at scale and equitably share the cluster with the aid of quotas- Operational aspects of running Kafka clusters at scale, performance tuning and methods for optimising network and storage utilisation- All aspects of Kafka security -including network segregation, encryption, certificates, authentication and authorization.The coverage is progressively delivered and carefully aimed at giving you a journey-like experience into becoming proficient with Apache Kafka and Event-Driven Architecture. The goal is to get you designing and building applications. And by the conclusion of this book, you will be a confident practitioner and a Kafka evangelist within your organisation - wielding the knowledge necessary to teach others.