![matthias-wessendorf.png](/sites/default/files/styles/author_full/public/matthias-wessendorf.png?itok=A9muGnRf)
Senior Principal Software Engineer, Red Hat
Matthias Wessendorf
Matthias Wessendorf works on the Messaging team at Red Hat, focusing on event-driven architectures, data-streaming, and serverless workloads. He is an active contributor to the Knative project. Matthias is a regular speaker at international conferences and is a long standing member of the Apache Software Foundation.
Matthias Wessendorf's contributions
Article
How to set up event-driven microservices using Knative Eventing
Matthias Wessendorf
Learn how to set up event-driven microservices using Knative Eventing and CloudEvents to simplify EDA-style application development.
Article
Our advice for configuring Knative Broker for Apache Kafka
Matthias Wessendorf
This article discusses configuration best practices and recommendations for the Knative Broker implementation for Apache Kafka, which is now GA.
Article
How Knative broker GA enhances Kafka on OpenShift Serverless
Matthias Wessendorf
Learn how to produce and consume messages efficiently using the Knative implementation (which is now available) in Red Hat OpenShift Serverless.
Article
Serverless Kafka on Kubernetes
editorial-team
+1
In this session, we will walk through an end-to-end demo, showing the lifecycle of an event-driven application based on Apache Kafka.
Article
EventFlow: Event-driven microservices on Red Hat OpenShift (Part 2)
Hugo Hiden
+2
Learn how to deploy the EventFlow management platform on Red Hat OpenShift, install a set of sample processors, and build a flow.
Article
Processing CloudEvents with Eclipse Vert.x
Matthias Wessendorf
How to generate or process CloudEvents using Vert.x. CloudEvents describe event data in a common, standardized way based on a spec from CNCF
Article
EventFlow: Event-driven microservices on OpenShift (Part 1)
Hugo Hiden
+2
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.
Article
Smart-Meter Data Processing Using Apache Kafka on OpenShift
Hugo Hiden
+2
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.
![cloudevents](/sites/default/files/styles/list_item_thumb/public/CloudEventsJs_2x_1.png?itok=8jInJj78)
How to set up event-driven microservices using Knative Eventing
Learn how to set up event-driven microservices using Knative Eventing and CloudEvents to simplify EDA-style application development.
![Building resilient event-driven architectures with Apache Kafka](/sites/default/files/styles/list_item_thumb/public/blog/2021/05/kafka-event-driven_2x.png?itok=FjeOmO-q)
Our advice for configuring Knative Broker for Apache Kafka
This article discusses configuration best practices and recommendations for the Knative Broker implementation for Apache Kafka, which is now GA.
![Image featuring red hat, lightning bolt, and gears](/sites/default/files/styles/list_item_thumb/public/blog/2020/12/openshift-serverless-fucntions_1x.png?itok=8Ef374Am)
How Knative broker GA enhances Kafka on OpenShift Serverless
Learn how to produce and consume messages efficiently using the Knative implementation (which is now available) in Red Hat OpenShift Serverless.
![Kafka-serverless Serverless Kafka](/sites/default/files/styles/list_item_thumb/public/blog/2019/12/Kafka-serverless.png?itok=sCQUKoAj)
Serverless Kafka on Kubernetes
In this session, we will walk through an end-to-end demo, showing the lifecycle of an event-driven application based on Apache Kafka.
![EventFlow EventFlow](/sites/default/files/styles/list_item_thumb/public/blog/2019/05/EventFlow.png?itok=7EMTyhwh)
EventFlow: Event-driven microservices on Red Hat OpenShift (Part 2)
Learn how to deploy the EventFlow management platform on Red Hat OpenShift, install a set of sample processors, and build a flow.
![Eclipse Vert.x 3.8.1 update for Red Hat OpenShift Application Runtimes Eclipse Vert.x](/sites/default/files/styles/list_item_thumb/public/blog/2018/12/Vert.x_Logo.png?itok=fkfkRfWo)
Processing CloudEvents with Eclipse Vert.x
How to generate or process CloudEvents using Vert.x. CloudEvents describe event data in a common, standardized way based on a spec from CNCF
![Blog Post_ CloudEvent Flow_Full CloudEvent Flow](/sites/default/files/styles/list_item_thumb/public/blog/2018/10/Blog-Post_-CloudEvent-Flow_Full.png?itok=-EYYsoJw)
EventFlow: Event-driven microservices on OpenShift (Part 1)
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.
![Apache Kafka on OpenShift](/sites/default/files/styles/list_item_thumb/public/blog/2018/07/kafka-logo-wide.png?itok=AqRR0I3i)
Smart-Meter Data Processing Using Apache Kafka on OpenShift
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.