Matthias Wessendorf

Learn how to set up event-driven microservices using Knative Eventing and CloudEvents to simplify EDA-style application development.

This article discusses configuration best practices and recommendations for the Knative Broker implementation for Apache Kafka, which is now GA.

Learn how to produce and consume messages efficiently using the Knative implementation (which is now available) in Red Hat OpenShift Serverless.

In this session, we will walk through an end-to-end demo, showing the lifecycle of an event-driven application based on Apache Kafka.

Learn how to deploy the EventFlow management platform on Red Hat OpenShift, install a set of sample processors, and build a flow.

How to generate or process CloudEvents using Vert.x. CloudEvents describe event data in a common, standardized way based on a spec from CNCF

This post is the first in a series that describes a lightweight cloud-native distributed microservices framework called EventFlow that targets the Kubernetes/OpenShift platforms and models event-processing applications as a connected flow or stream of components. EventFlow can be used to develop event-processing applications that can process CloudEvents, which are an effort to standardise upon a data format for exchanging information regarding events generated by cloud platforms.

Learn how to process and aggregate huge streams of IoT data using Strimzi and Apache Kafka on Red Hat OpenShift. The data stream is processed using the Red Hat AMQ distributed streaming platform to perform aggregations in real time as data is ingested into the application.