Hi, and welcome to our final module, which will be focused on Jupyter Hub.
What we'll learn in this module, this module will be, uh, short,
but we'll learn how to launch our own Jupyter Hub on our laptop via
Docker.
We'll learn the basics about Jupyter Hub configuration and we'll learn how to
manage Jupyter Hub users.
I'm sure you already noticed that in previous modules when we have launched our
Jupyter Server, it was a single user Jupyter Notebook.
We could use it from, uh, multiple places like browsers,
and also we could log into the same Jupyter server from different computer on
the same network like your Homeland, for example. Maldi,
we always using it as a single user without the possibility to log in as another
user. And exactly for this is the Jupyter app.
It provides as a way to create a centralized deployment of Jupyter for multiple
users, which have their own running Jupyter Server.
They can use it concurrently, and they also have, uh,
their own logging information. Unlike the username and password,
administrators can manage users and distribute resources accordingly between
users or group. Jupyter Hub is, uh, highly customizable.
It can be used in a variety of environments.
It supports many kernels and, uh, can be used to serve Jupyter Notebooks,
Jupyter Lab, or Earth Studio or others.
You can create your Jupyter Hub for just few users on your local
line network, but you can scale it to thousands of users when deployed on cloud.
Uh, using Kubernetes for example, it provides, uh,
multiple identification options and it's entirely open source.
Jupyter Hub has few key components. The Hub, uh,
this is a central process which manages user notification.
It coordinates pounding of single user servers and provides a control panel for
the users proxy.
Endless web traffic and routes requests to the hub and to the single user
servers.
Palms are responsible for launching single user Jupyter Instances.
Identifi define how users should authenticate.
Jupyter Hub provides identification using multiple methods like S L D A P,
local system accounts and others. The,
these are extensions of Jupyter Hub for various tasks for integrating
third party tools or others.
Jupyter Hub provides multiple deployment options on a local server. Uh,
we'll do exactly this, but in combination with Docker, uh,
where we will create our own Jupyter Hub server on our laptop.
You can deploy Jupyter Hub into cloud using various providers.
You can also deploy Jupyter Hub using Docker,
but you can also install it directly onto the system. Uh,
Jupyter Hub is basically like any other Python package, like Jupyter Lab,
for example.
And also you can use high Performance computing clusters for deployment as well.
In our next video, we will launch our Jupyter Hub from Blocker.