Distributed event streaming platform used by thousands of companies for high-performance data pipelines, streaming analytics, and mission-critical applications. Kafka’s publish-subscribe messaging system handles real-time data feeds at massive scale, providing fault tolerance and durability. Whether you’re building a microservices architecture, tracking user activity, or processing financial transactions, this section offers tutorials, best practices, and deep dives to help you master Kafka’s core components: Producers, Consumers, Brokers, Topics, and Partitions.
Apache Kafka Streams is a client-side library for building applications and microservices that process and analyze data stored in Kafka topics. It combines the simplicity of writing and deploying standard Java/Scala applications with the power of Kafka’s immutable log, enabling sophisticated stream processing with native fault tolerance and scalability. KStream […]
In a production Kafka environment, data quality and backward compatibility are not optional, they are critical requirements. Simply serializing data as JSON or raw bytes is a fast track to chaos, especially in microservices architectures where producers and consumers evolve independently. The Confluent Schema Registry provides the solution: a centralized […]