Temporary link (scan and close) for immersion day April 2017
Welcome! Cloud 101/102 is a half-day hands-on introduction to moving your research computing to the public cloud. We present each of the three major cloud providers on a level playing field. They share many similarities; and each cloud has its unique advantages that we hope to highlight. In all cases we are working with the cloud providers -- Microsoft, Google and Amazon Web Services -- to give you the best initial view into what these remarkable platforms are capable of.
As always with our cloud computing program our emphasis is on you the Researcher. If you decide to investigate the cloud as a computing environment: You are signing up to climb a learning curve as well as to take on a set of responsibilities. There is no easy way around this but we believe that this process could very well accelerate your research; so it is our pleasure to provide this opportunity for an initial inquiry.
For each day we will follow a simple template that begins with the "101" basics before lunch and then brings in some "102" introductory material on data science tools in the early afternoon. This GitHub repo covers the spectrum as follows:
- This page is the basic outline of 101/102 for all three clouds with links
- Each cloud has a "notes" page (AWS.md, Azure.md, GCP.md) reflecting on the process for each
What is the cloud and what is it good for? We will run through the following topics in about two and a half hours:
- What is the cloud in three words or less?
- Cloud jargon and how it works for you
- Consoles versus commands versus api's
- The Console / Portal
- Instances: Create, log in, update, modify, stop, image, start from image, verify, cost
- Storage: Block, object, archival; write from world, read to Instance
- Services: Databases, serverless computing and much more
- Scale: How cloud auto-scaling features map to research computing
- Cost estimation and cost management
- Data-oriented and sandbox-oriented collaboration
What makes each cloud unique? And how do they support data science? This section after lunch is intended to provide a basic introduction (feasibility demonstration) for data science on each respective cloud.
- Machine Learning
- Jupyter environments and open science