Using Docker with Jupyter

Docker is a mechanism that allows you to have many complete virtual instances of an application in one machine. Docker is used by many software firms to provide a fully scalable implementation of their services, and support as many concurrent users as needed.

Prior mechanisms for dealing with multiple instances shared common resources (such as disk address space). Under Docker, each instance is a complete entity separate from all others.

Implementing Jupyter on a Docker environment allows multiple users to access their own Jupyter instance, without having to worry about interfering with someone else's calculations.

The key feature of Docker is allowing for a variable number of instances of your notebook to be in use at any time. The Docker control system can be set up to create new instances for every user that accesses your notebook. All of this is built-in to Docker without programming; just use the user interface to decide how to create instances.

There are two ways you can use Docker:

• From a public service
• Installing Docker on your machine