your task is very very broad you mention you don't want to deal with AWS, if it's because of ad-hoc installation concerns and nothing else you can just run you

your task is very very broad you mention you don't want to deal with AWS, if it's because of ad-hoc installation concerns and nothing else you can just run your notebooks in ready-made solutions like Google Colab, or Jupyter-book in Github ( https://github.com/executablebooks/jupyter-book https://github.com/executablebooks/jupyter-book )) that would cover a lot of use cases right away without next to no learning curve If you don't want to deal with AWS or similar, in that case: - if it's a static notebook then you can obviously render it and serve the web content (might seem obvious but needs to be considered) - if it's dynamic but has light hardware requirements, you can try jupyterlite which runs in the browser and should do a pyodine (webassembly CPython kernel) can do: https://jupyterlite.readthedocs.io/en/latest/try/lab/ https://jupyterlite.readthedocs.io/en/latest/try/lab/ - otherwise, you can try exposing a dockerised jupyter env ( as in https://github.com/MKAbuMattar/dockerized-jupyter-notebook/blob/main/docker-compose.yml https://github.com/MKAbuMattar/dockerized-jupyter-notebook/b... ) or even better a nixified one ( https://github.com/tweag/jupyenv https://github.com/tweag/jupyenv ) there might be other approaches I'm missing, but I think that's pretty much it that doesn't entail some proprietary solution or an ad-hoc installation as you've been doing