Senior Engineering Manager
Simon Woodman
Simon manages the products within Red Hat's data streaming ecosystem, such as Streams for Apache Kafka. Engineers on his team are drive innovation in Apache Kafka, Strimzi, Kroxylicious and other Open Source projects.
Simon Woodman's contributions
Article
Open innovation: Red Hat’s impact on the Kafka and Strimzi ecosystem
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.
Article
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.
Article
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.
Article
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.
Open innovation: Red Hat’s impact on the Kafka and Strimzi ecosystem
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.
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.
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.
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.
