Stream processing: Continuous data management in real time

Stream processing lets developers view, analyze, and combine data from a wide variety of sources.

More streams processing resources

Building resilient event-driven architectures with Apache Kafka
Article
Nov 27, 2024

Dynamic Kafka controller quorum

Federico Valeri +1

This article explores use cases for the dynamic quorum configuration in Kafka...

Building resilient event-driven architectures with Apache Kafka
Article
Jul 30, 2024

Set up a streams for Apache Kafka cluster with Ansible

Romain Pelisse

Deploy a fully functional streams for Apache Kafka cluster in an automated...

Featured image: event-driven distributed serverless workflow
Article
Jul 02, 2024

Build an extendable multichannel messaging platform

Bruno Meseguer

This solution demonstrates an implementation to build a platform that...

Building resilient event-driven architectures with Apache Kafka
Article
Jun 26, 2024

Open innovation: Red Hat’s impact on the Kafka and Strimzi ecosystem

Simon Woodman

Open source is at the heart of everything Red Hat works on. Learn how Red Hat...

Stream processing resources

Building resilient event-driven architectures with Apache Kafka
Article

Dynamic Kafka controller quorum

Federico Valeri +1

This article explores use cases for the dynamic quorum configuration in Kafka that allows KRaft clusters to scale controller nodes without downtime.

Runtimes
Article

Ansible Collection for Red Hat Runtimes

Romain Pelisse

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

More stream processing resources