Stream Processing in Kubernetes: practical guide
How should the modern distributed data processing look like? It should definitely be fast, real-time, and so easy to use that you could understand its basics in less than 1 hour! In this hands-on session I’ll present the steps to use stream processing in Kubernetes.
You can expect the following agenda:
- Introduction to stream processing (in comparison to the good old batch processing)
- Setting up a Hazelcast Jet cluster in Kubernetes
- Running a sample distributed batch job
- Running a real-time stream processing application in Kubernetes
- Automatic scaling up/down of Jet cluster depending on the load
- Running more complex stream processing algorithms with data windowing and aggregations
You can either come and listen or join with your own laptop. The only requirement is to have access to a Kubernetes cluster (Minikube / Docker for Desktop is good enough). Welcome!