Stream processing: Continuous data management in real time

Ansible Collection for Red Hat Runtimes products comes in two different flavors: one upstream, one downstream. This article explores what this means exactly.

This solution demonstrates an implementation to build a platform that synthesizes conversations across multiple different communication channels and services.

Open source is at the heart of everything Red Hat works on. Learn how Red Hat engineers contribute to data streaming projects such as Apache Kafka and Strimzi.

Learn how to build an end-to-end reactive stream processing application using Apache Kafka as an event streaming platform, Quarkus for your backend, and a frontend written in Angular.

Get tips on managing and preserving Kafka Connect offsets smoothly starting from AMQ Streams 2.6 (Kafka 3.6).

Discover the importance of encryption of data at rest in Apache Kafka and examine one approach to encrypting data at rest using the Kroxylicious Kafka proxy.