jupyterhub-k8s | Data 8 's deployment of JupyterHub on Kubernetes | Learning library

by data-8 Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | jupyterhub-k8s Summary

jupyterhub-k8s is a Python library typically used in Tutorial, Learning, Ansible, Jupyter applications. jupyterhub-k8s has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However jupyterhub-k8s build file is not available. You can download it from GitHub.

Note that this repo is deprecated. If you want to deploy JupyterHub for your own use, please look at the Zero to JupyterHub guide which grew out of this repo!.

Support

Quality

Security

License

Reuse

Support

jupyterhub-k8s has a low active ecosystem.

It has 34 star(s) with 17 fork(s). There are 13 watchers for this library.

It had no major release in the last 6 months.

There are 22 open issues and 48 have been closed. On average issues are closed in 52 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of jupyterhub-k8s is current.

Quality

jupyterhub-k8s has 0 bugs and 0 code smells.

Security

jupyterhub-k8s has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

jupyterhub-k8s code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

jupyterhub-k8s is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

jupyterhub-k8s releases are not available. You will need to build from source code and install.

jupyterhub-k8s has no build file. You will be need to create the build yourself to build the component from source.

jupyterhub-k8s saves you 270 person hours of effort in developing the same functionality from scratch.

It has 655 lines of code, 42 functions and 8 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed jupyterhub-k8s and discovered the below as its top functions. This is intended to give you an instant insight into jupyterhub-k8s implemented functionality, and help decide if they suit your requirements.

Create an archive
Wait for an operation
Attach a disk to an instance
Delete a snapshot
Check if an operation exists
List all snapshots for a project
Retrieve the single single user image from kubectl
List all disks for a project
Get user from claim
Create a new disk from a snapshot
Count the number of pods in a given namespace
Return Kubernetes hub pod pod
Filter out snapshots that are older than retention_period
Returns the number of days between now and last backups
Filter disks by their names
Replace a snapshot with a new disk
Filter snapshots by their id
Create a snapshot of a disk
Delete a specific snapshot
Validate ACL for a given user
Get all GCE persistent disk names in a given namespace
Returns a list of all persistent volumes in the given namespace
Returns all PV names in a namespace
Create an SMTP connection
Generate the URL for a bucket

Get all kandi verified functions for this library.

jupyterhub-k8s Key Features

No Key Features are available at this moment for jupyterhub-k8s.

jupyterhub-k8s Examples and Code Snippets

No Code Snippets are available at this moment for jupyterhub-k8s.

Community Discussions

Trending Discussions on jupyterhub-k8s

How to migrate data from Google Cloud VM to Google Kubernetes Engine?

QUESTION

How to migrate data from Google Cloud VM to Google Kubernetes Engine?

Asked 2020-Sep-17 at 11:28

I am running JupyterHub on Google Cloud VM but due to some reasons I am not able to access JupyterHub running on VM now. Rather than resolving the issue with current JupyterHub I wanted to migrate JupyterHub on our Google Kubernetes Engine, so I installed another JupyterHub on Google Kubernetes Engine using zero-to-jupyterhub-k8s.

Now everything is running fine but I want to migrate the data saved on the old JupyterHub VM to my new JupyterHub. The new JupyterHub using Persistent Volume claims as storage for each of the pods of users. Could someone please let me know how can I do it?

...

ANSWER

Answered 2020-Sep-17 at 11:28

Posting this answer as a community wiki for a better visibility as well to add some additional resources that could help when encountered with similar scenario.

The issue portrayed in the question was resolved by copying user data to GCS bucket and then mounting the data to the user pods as posted in the comment:

I solved this issue by copying the data from the VM to Google Cloud Storage and then mounted the GCS Bucket on the user pods in JupyterHub on Google Kubernetes Engine.

The guide for installing zero-to-jupyterhub-k8s:

Resources on mounting GCS bucket to the Kubernetes pod:

Citing the Github page:

Disclaimer!

The big catch is that for this to work, the container has to be built with gcsfuse. The Dockerfile includes a base build for debian jessie.

The most note worthy parts of the configuration are the following:

Source https://stackoverflow.com/questions/63231663

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install jupyterhub-k8s

You can download it from GitHub.
You can use jupyterhub-k8s like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: