Practical Enterprise JupyterHub Deployment and MLOps with PrimeHub

This talk is intended for audience interested in larger scale Jupyter environment deployment in their organisation, particularly for machine learning applications.

PrimeHub is an open-source enterprise offering based on JupyterHub, addressing a few common hurdles:

• advanced resource scheduling for heterogenous GPU clusters
• multi-tenancy and project isolations

• customizable and consistent ML environments per project

• hybrid development environment such as vscode and ssh within notebook instances
• authorization and data access management

• operating in on-premises / hybrid / air-gapped environments

We also investigate a few trends adjacent to the day-to-day jupyter environment used by data scientists and data engineers, where the roles become more cross functional in the age of MLOps:

• working with job schedulers from within Notebook

• managing ML model deployments

github: https://github.com/infuseai/primehub