I'll reply to both you and OP here. I have an open bug on this as well. The closest thing I have found is
http://blog.ibmjstart.net/2016/01/28/jupyter-notebooks-as-re...Jupiter is brilliant to prototype stuff - anything from metric dashboards to ML models. The problem is how do you take this live ?
So you have production engineers transforming this code into a microservice and then writing an exact duplicate dashboard in reactjs or something. Why ? Because jupyter spawns kernel which is directly related to state of execution of the program...So if I'm logged into the dashBoard, nobody else can.
Instead, if you could nbconvert the notebook into flask code, I could have a running dashboard in a piece of flask code that I can immediately put on my server.
I will pay for this - both because it is very useful, and also as a way for me to fund something cool.
As a business model, it is damn cool - this is true heroku for data scientists.
EDIT: incidentally I have been told by many people to switch to Zeppelin. Apparently, it works nicer at building dashboard..And More importantly, it is seamless integrated with the spark ecosystem (including cluster support) that makes scaling very easy. GCP Dataproc comes with recipes to launch Zeppelin on the server.