Cloud Pre-Exercise

A physics analysis usually encompasses running over hundreds of gigabytes of data. At CMS, this is usually performed using high-throughput batch systems such as the HTCondor installation at CERN and at other research institutions as well as the worldwide LHC computing grid (WLCG). Not everyone will have these resources available at their own institution, but nowadays anyone can get access to computing resources via public cloud vendors. This lesson will give you prepare you an environment for running realistic physics analyses “in the cloud” using Kubernetes (as well as giving you a brief introduction to Kubernetes itself).

Prerequisites

You should be familiar with Docker and the Shell

Schedule

Setup Download files required for the lesson
00:00 1. Introduction What is Kubernetes?
What is a Kubernetes cluster and why do I need one?
What is Argo?
00:10 2. Getting started with Argo and Kubectl How to use Kubectl commands?
What is kubectl?
What is Argo workflows?
00:20 3. Demo: Creating a cluster What are the basic concepts and jargon I need to know?
Do do I manually create a K8s cluster on the GCP
00:45 4. Demo: Storing a workflow output on Kubernetes How to setup a workflow engine to submit jobs?
How to run a simple job?
How can I set up shared storage for my workflows?
How to run a simple job and get the the ouput?
01:20 5. Demo: Deploy a Webserver How can I visualize my workflows?
How do I deploy my Argo GUI?
01:45 6. Cleaning up How do I clean my workspace?
How do I delete my cluster?
02:00 Finish

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.