Matthias Wessendorf

Matthias works at Red Hat on the messaging team with a focus on modern data streaming platforms. He is a contributor to many Open Source projects and likes speaking at international conferences

Recent Posts

Processing CloudEvents with Eclipse Vert.x

Processing CloudEvents with Eclipse Vert.x

Our connected world is full of events that are triggered or received by different software services. One of the big issues is that event publishers tend to describe events differently and in ways that are mostly incompatible with each other.

To address this, the Serverless Working Group from the Cloud Native Computing Foundation (CNCF) recently announced version 0.2 of the CloudEvents specification. The specification aims to describe event data in a common, standardized way. To some degree, a CloudEvent is an abstract envelope with some specified attributes that describe a concrete event and its data.

Working with CloudEvents is simple. This article shows how to use the powerful JVM toolkit provided by Vert.x to either generate or receive and process CloudEvents.

Continue reading “Processing CloudEvents with Eclipse Vert.x”

Share
EventFlow: Event-driven microservices on OpenShift (Part 1)

EventFlow: Event-driven microservices on OpenShift (Part 1)

This post is the first in a series of three related posts that describes a lightweight cloud-native distributed microservices framework we have created called EventFlow. EventFlow can be used to develop streaming applications that can process CloudEvents, which are an effort to standardize upon a data format for exchanging information about events generated by cloud platforms.

The EventFlow platform was created to specifically target the Kubernetes/OpenShift platforms, and it models event-processing applications as a connected flow or stream of components. The development of these components can be facilitated through the use of a simple SDK library, or they can be created as Docker images that can be configured using environment variables to attach to Kafka topics and process event data directly.

Continue reading “EventFlow: Event-driven microservices on OpenShift (Part 1)”

Share
Smart-Meter Data Processing Using Apache Kafka on OpenShift

Smart-Meter Data Processing Using Apache Kafka on OpenShift

There is a major push in the United Kingdom to replace aging mechanical electricity meters with connected smart meters. New meters allow consumers to more closely monitor their energy usage and associated cost, and they enable the suppliers to automate the billing process because the meters automatically report fine-grained energy use.

This post describes an architecture for processing a stream of meter readings using Strimzi, which offers support for running Apache Kafka in a container environment (Red Hat OpenShift). The data has been made available through a UK research project that collected data from energy producers, distributors, and consumers from 2011 to 2014. The TC1a dataset used here contains data from 8,000 domestic customers on half-hour intervals in the following form:

Continue reading “Smart-Meter Data Processing Using Apache Kafka on OpenShift”

Share
Introducing the Kafka-CDI Library

Introducing the Kafka-CDI Library

Using Apache Kafka in modern event-driven applications is pretty popular. For a better cloud-native experience with Apache Kafka, it’s highly recommended to check out Red Hat AMQ Streams, which offers an easy installation and management of an Apache Kafka cluster on Red Hat OpenShift.

This article shows how the Kafka-CDI library can handle difficult setup tasks and make creating Kafka-powered event-driven applications for MicroProfile and Jakarta EE very easy.

Continue reading “Introducing the Kafka-CDI Library”

Share