For many of the more involved processing labs of this class, we will be using a cloud-based Lab Environment. Using such a cloud-based lab has numerous advantages over physical computer pools. It will come pre-installed with all relevant processing tools and spare you the painful trouble of installing each individual package by hand. It will also ensure that all lab machines are identical. This ensures similar processing speed at all work stations and identical software behavior for all participants. Finally, we will ensure that all machines are correctly scaled, so that you can complete your assignments in a timely manner without ever running out of space.
The Cloud-Based Lab:
To perform the labs for this class, we will be using a JupyterHub server running in the cloud. The cloud provider we’re using is AWS (Amazon Web Services), but for the most part you’ll be interacting with the JupyterHub and the Jupyter Notebooks that you create using the hub and the materials provided.
Before the first lab that uses the Jupyter Notebooks, you’ll be given a URL for the JupyterHub. When you visit that URL, you’ll have to enter a username and a password. These will also be provided. Once you have authenticated, the JupyterHub server will start up a separate server for your Jupyter Notebook. This last part can take a minute or two. Once the Notebook is started you’ll be able to perform the steps from the lab materials, and these commands will be run by Notebook server in the cloud.