JupyterHub Spawner for Kubernetes
Project description
kubespawner (jupyterhub-kubespawner @ PyPI)
The kubespawner (also known as JupyterHub Kubernetes Spawner) enables JupyterHub to spawn single-user notebook servers on a Kubernetes cluster.
See the KubeSpawner documentation for more information about features and usage. In particular, here is a list of all the spawner options.
Features
Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications. If you want to run a JupyterHub setup that needs to scale across multiple nodes (anything with over ~50 simultaneous users), Kubernetes is a wonderful way to do it. Features include:
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Easily and elasticly run anywhere between 2 and thousands of nodes with the same set of powerful abstractions. Scale up and down as required by simply adding or removing nodes.
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Run JupyterHub itself inside Kubernetes easily. This allows you to manage many JupyterHub deployments with only Kubernetes, without requiring an extra layer of Ansible / Puppet / Bash scripts. This also provides easy integrated monitoring and failover for the hub process itself.
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Spawn multiple hubs in the same kubernetes cluster, with support for namespaces. You can limit the amount of resources each namespace can use, effectively limiting the amount of resources a single JupyterHub (and its users) can use. This allows organizations to easily maintain multiple JupyterHubs with just one kubernetes cluster, allowing for easy maintenance & high resource utilization.
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Provide guarantees and limits on the amount of resources (CPU / RAM) that single-user notebooks can use. Kubernetes has comprehensive resource control that can be used from the spawner.
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Mount various types of persistent volumes onto the single-user notebook's container.
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Control various security parameters (such as userid/groupid, SELinux, etc) via flexible Pod Security Policies.
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Run easily in multiple clouds (or on your own machines). Helps avoid vendor lock-in. You can even spread out your cluster across multiple clouds at the same time.
In general, Kubernetes provides a ton of well thought out, useful features - and you can use all of them along with this spawner.
Requirements
JupyterHub
Requires JupyterHub 4.0+
Kubernetes
Everything should work from Kubernetes v1.24+.
The Kube DNS addon is not strictly required - the spawner uses environment variable based discovery instead. Your kubernetes cluster will need to be configured to support the types of volumes you want to use.
If you are just getting started and want a kubernetes cluster to play with, Google Container Engine is probably the nicest option. For AWS/Azure, kops is probably the way to go.
Getting help
We encourage you to ask questions on the Jupyter mailing list. You can also participate in development discussions or get live help on Gitter.
License
We use a shared copyright model that enables all contributors to maintain the copyright on their contributions.
All code is licensed under the terms of the revised BSD license.
Resources
JupyterHub and kubespawner
Jupyter
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