Glad it looks interesting to you! Regarding running a Kubernetes cluster, that's only required if you want the steps in your pipeline to all execute in their own containers. If your workflow is such that everything can run on a single machine, you can still use Sematic to track your experiments. One advantage here is that if you ever do need to scale up to containerized workflows, you can do so without changing the code for your pipeline.