Streaming data represents a constant flow of events. One example might be a newer-generation car. Every time the location of the car changes, a new event is created. It’s called "streaming data" because there are thousands of these events resulting in a constant stream of data. Such data should be processed incrementally using stream processing techniques and technologies that allow you to handle the high throughput.

In this session, we will show you how to implement such a use-case with Java and developer productivity in mind using a modern application platform on Kubernetes and a workflow engine to maintain state and handle errors in event-driven microservice architectures.

We will leverage the capabilities of the VMware Tanzu Application Platform based on famous OSS projects like Knative and Camunda’s workflow engine Zeebe to be able to focus on the implementation of the actual business logic with the Spring ecosystem.