This lesson is in the early stages of development (Alpha version)

Cloud Computing

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 a first taste of running realistic physics analyses workflows “in the cloud” using Kubernetes (as well as giving you a brief introduction to Kubernetes itself and some related tools).

Prerequisites

We expect you to have followed the largest part of this workshop. In particular, you should be familiar with Docker by now.

Schedule

Setup Before you begin
00:00 1. Prep-work: Kubernetes Clusters What is Kubernetes?
What is a Kubernetes cluster and why do I need one?
00:00 2. See you tomorrow Key question (FIXME)
00:00 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
00:20 4. Kubectl and additional tools and services What is kubectl?
What is Argo workflows?
What kind of services/resources will I need to instantiate in my cluster?
00:40 5. See you tomorrow
00:40 6. Hands-on: Accessing your K8s cluster How do I join the GCP project for these hands-on activities?
What GCP resources do I have?
How do I connect to my cluster?
01:25 7. Break
01:25 8. Hands-on: Running and understanding Argo workflows How are Argo workflows configured?
What are the main ingredients of an Argo yaml workflow file?
02:05 Finish

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