Bob Sinkovits and I are presenting a paper at PEARC18 about:
"Deploying Jupyter Notebooks at scale on XSEDE resources for Science Gateways and workshops"
See the pre-print on Arxiv: https://arxiv.org/abs/1805.04781
Jupyter Notebooks provide an interactive computing environment well suited for Science. JupyterHub is a multi-user Notebook environment developed by the Jupyter team.
In order to provide adequate amount of memory and CPU to many users for example during workshops, it is necessary to leverage a distributed system, either leveraging multiple Jetstream instances or interfacing with a traditional HPC system.
In this work we present 3 strategies for deploying JupyterHub on XSEDE resources to support a large number of users, each is linked to the step-by-step tutorial with all necessary configuration files:
- deploy Jupyterhub on a single Jetstream instance and spawn Jupyter Notebook servers for each user on a computing node of a Supercomputer (for example Comet)
- deploy Jupyterhub on Jetstream using Docker Swarm to distributed the user's containers across many instances and providing persistent storage with quotas through a NFS share
- deploy Jupyterhub on top of Kubernetes across Jetstream instances with persistent storage provided by the Ceph distributed filesystem
If are an author at PEARC18, you can follow my instructions on how to publish your preprint to Arxiv