Glossary

Key Points

Introduction	Kubernetes is an orchestrator of containers. It is most useful when it is run in a cluster of computers. Commercial K8s clusters are a good option for large computing needs. We can run our containerized CMSSW jobs and subsequent analysis workflows in a K8s cluster.
Getting started with Argo and Kubectl	`kubectl` is the ruler of GKE Argo is a very useful tool for running workflows and parallel jobs To be able to write, read and extract data, a few services/resources need to be set up on the GCP
Demo: Creating a cluster	It takes just a few clicks to create you own K8s cluster
Demo: Storing a workflow output on Kubernetes	With Kubernetes one can run workflows similar to a batch system Open Data workflows can be run in a commercial cloud environment using modern tools
Demo: Deploy a Webserver	With a simple but a tight yaml structure, a full-blown analysis can be performed using the Argo tool on a K8s cluster.
Cleaning up	Cleaning your workspace in periods of time while you’re not running workflows will save you money. With a couple commands it is easy to get back to square one.

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