For anyone in 2019 looking to do this, we built a prototype here: 
https://github.com/tamera-lanham/ipython-kernel-docker

Similar to the approach in the Gist, except instead of a Python file 
running the container, we tell Jupyter to do it instead. 

On Tuesday, July 10, 2018 at 4:01:53 AM UTC-4, Ken Jiiii wrote:
>
> Hi guys,
>
> I think I have the same use case and I was wondering whether this 
> discussion is still up to date.
> The idea is to have a Jupyter running on a local machine which has one or 
> more docker containers running at the same time. These containers provide 
> for example different python versions like 3.6 and 3.7.
> Now the question is how to add an external kernel to Jupyter. The kernel 
> is of course running in the docker container.
>
> https://gist.github.com/mariusvniekerk/09062bc8974e5d1f4af6 is this 
> approach still valid @ Marius?
>
> I have also read that it is possible to connect via ssh to a remote kernel 
> in Jupyter but in that case SSH needs to be configured in the container.
>
> Can anybody tell me what solution is still working for him?
>
> Thanks a lot in advance and kind regards!
>
> Am Mittwoch, 26. Juli 2017 14:23:08 UTC+2 schrieb Ashwin Srinath:
>>
>> We have used Singularity (http://singularity.lbl.gov/) containers in 
>> Jupyter Notebooks with relative ease. Some notes available here:
>>
>> https://github.com/clemsonciti/singularity-in-jupyter-notebook
>>
>> Thanks,
>> Ashwin
>>
>> On Tue, Jul 25, 2017 at 5:10 AM, Stojan Jovanović wrote:
>>
>>> Hi James,
>>>
>>> I'm currently buidling something very similar to what you're talking 
>>> about.
>>>
>>> I've currently got it set up so that I can access multiple Dockers, 
>>> containing isolated machine learning models, through a Jupyter notebook 
>>> (located in a third Docker), via SSH. 
>>>
>>> It wasn't super difficult to do, although I'm not claiming it was done 
>>> very elegantly. 
>>>
>>> If you're interested, you can take a look here 
>>> https://github.com/stojan211287/DockerSSH. I've uploaded a minimal 
>>> example, consisting of one "drone" and one "overlord" container. The 
>>> overlord issues commands via SSH, the drone complies and delivers.
>>>
>>> As it stands now, I've based the images on Alpine 3.6 and am currently 
>>> using them as base images for further development.- the overlord get 
>>> Jupyter installed on top of it, and the drone, for example, can host 
>>> scikit-learn.
>>>
>>> On Wednesday, 24 May 2017 23:10:34 UTC+2, James wrote:
>>>>
>>>> Hey, sorry to revive this thread again, but having docker container 
>>>> kernels (and not whole jupyter server systems) would be very useful for 
>>>> me.  My use case is having certain hard to build scientific software 
>>>> installed within the container.  That way you could call out to them using 
>>>> python's subprocess calls from within the notebook.  My goal would be to 
>>>> make several kernels, accessible from the same notebook server, to act as 
>>>> a 
>>>> toolkit of sorts for my lab.  Ideally having the kernels in containers 
>>>> would make them easy to share and install in sister labs at other 
>>>> institutions for use in their Jupyter ecosystem.  Thank you for any 
>>>> guidance!
>>>>
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