# Jupyter kernels as a service

**URL:** https://forum.access-hive.org.au/t/jupyter-kernels-as-a-service/224
**Category:** Technical
**Tags:** python, jupyter
**Created:** [1 December 2022 23:04 UTC](https://forum.access-hive.org.au/t/jupyter-kernels-as-a-service/224 "2022-12-01T23:04:51Z")
**Posts on this page:** 2
**Page:** 1

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### Author: ![Aidan](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/aidan/32/42_2.png) [@Aidan](https://forum.access-hive.org.au/u/Aidan)
#### Post date: [1 December 2022 23:04 UTC](https://forum.access-hive.org.au/t/jupyter-kernels-as-a-service/224/1 "2022-12-01T23:04:51Z")

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Only a proof of concept, but this is interesting

> **[GitHub - davidbrochart/jupyter\_server\_kernels\_proxy: A Jupyter Server...](https://github.com/davidbrochart/jupyter_server_kernels_proxy)**
>
> A Jupyter Server Extension Proxying Kernels. Contribute to davidbrochart/jupyter\_server\_kernels\_proxy development by creating an account on GitHub.

The idea is to run the kernel on one machine, and the jupyterlab instance on another.

A specific use case: run the kernel on a gadi PBS job and the jupyterlab instance on your laptop.

How is this different to [OOD](https://ood.nci.org.au)/[ARE](https://are.nci.org.au)? Well it means the notebook session is persistent on your local machine, the kernel dies and you can restart it and reconnect, but notebook remains. And you can mix notebooks with remote kernels and local ones.

It also means you can use other client to connect to the kernel, like [VS Code](https://code.visualstudio.com). Maybe this is useful to you @atteggiani?

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### Author: ![dougiesquire](https://sea2.discourse-cdn.com/flex020/user_avatar/forum.access-hive.org.au/dougiesquire/32/16_2.png) [@dougiesquire](https://forum.access-hive.org.au/u/dougiesquire)
#### Post date: [2 December 2022 00:29 UTC](https://forum.access-hive.org.au/t/jupyter-kernels-as-a-service/224/2 "2022-12-02T00:29:42Z")

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If this can play nicely with something like the [nb\_conda\_kernels extension](https://github.com/Anaconda-Platform/nb_conda_kernels), that would make for a very convenient workflow…
