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Comment by sandGorgon | Hacker News Reader

there is Dash (https://plot.ly/products/dash/) and there is Jupyter.

I wish there was some abstraction to generate a Dash like output from Jupyter. There are a lot of people who would pay serious money for that.

Even Airbnb built a framework to extract code from Jupyter notebooks and push them into a machine learning pipeline (https://medium.com/airbnb-engineering/using-machine-learning...).

Jupyter can be so much more by going closer to how it fits within a production pipeline versus just competing against Rstudio.

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There have been a couple attempts to add dashboarding to Jupyter:

https://github.com/jupyter/dashboards was/is a dashboard system built by a team at IBM. I think the project stalled somewhat after IBM stopped funding it.

There are a few long threads in the currently active jupyter repos about building dashboard systems as extensions: https://github.com/jupyterlab/jupyterlab/issues/1640, https://github.com/jupyter-widgets/ipywidgets/issues/2018.

I was searching for such dashboard utility and I found this: https://github.com/oschuett/appmode It may be useful for some of the cases.

> I wish there was some abstraction to generate a Dash like output from Jupyter. There are a lot of people who would pay serious money for that.

Notebook-to-dataviz is the value proposition of Mode Analytics, which has been doing well: https://modeanalytics.com/

Also I always thought notebooks would be a great devops tool, kind of like a super command line that has easily observable steps grouped in chunks and graphical feedback. No one else seems to think so though so maybe I'm wrong.

That makes good sense, in case it helps your confidence.

It's a middle ground between literate programming and a traditional IDE and there is nothing like that aimed at the ops space where it would actually be quite valuable.

emacs' org-mode / org-babel is well suited for it. This blog post [1] has some fantastic examples. The problem, of course, is that it's so closely tied to emacs.

1: http://howardism.org/Technical/Emacs/literate-devops.html

Nice, I just posted the video from that link above ;) Great minds think alike!

Howard's blog and github are an amazing resource; I'm a huge fan of his demo-it package as well. Highly recommend checking it out if you ever give technical presentations or talks.

As disclaimer/context, am a dev on the Azure hosted Jupyter Notebooks product,

You're not wrong! (Or at the least, it's a topic that has come across our ears before, and is something I certainly agree with) Obviously I probably shouldn't go off spouting all the pipe dreams I have in this space, but given that I got my start doing Ops work and tried to keep an eye for things I might have liked back then, I can assure you there you're not alone.

I always saw the similarity foremost as a direct upgrade to the "runbooks"/"firefighting/deploy checklists" that crop up all too often.

Another Azure dev checking in :)

Have you seen Application Insights Workbooks [0]? Basically you can have interactive notebooks and run analytics queries against your telemetry, generate charts, add text cells, etc. It's picking up usage for investigating outages, e.g., have a Workbook with a query that looks at your dependency calls and determine what service is failing + produce a visualization.

Workbooks don't actually execute any external actions, though. It's solely an analysis tool. Runbooks skew the other direction, they are for executing scripts (more or less).

Jupyter/python seems to fit in a nice gap where this could be bridged, especially with the level of existing python support from azure sdk + cli.

PS: a dev from Workbooks has seen Azure Notebooks, and was curious a while back about how he could integrate the functionality [1]

[0]: https://docs.microsoft.com/en-us/azure/application-insights/... [1]: http://blog.my-is300.com/2017/06/what-i-work-on-application-...

wow, a link to my blog (that second link) made hackernews? that's exciting!

Anyway, yeah, workbooks in appinsights is almost like notebooks for non-programmers? kinda? you string together markdown, parameters, and analytics queries (and very soon metrics across more of azure) into reports. But the parameters stuff lets you do more interactive things to hide/show sections now. i really need to do a new blog post about all the new stuff that's in there that wasn't last june!

i've prototyped some stuff to export an AI workbook to an azure/jupyter notebook, as there's some support for querying analytics already from a python package. there just hasn't been enough demand for it so far (not as much as we expected, anyway?)

How about Emacs + org mode? https://www.youtube.com/watch?v=dljNabciEGg

I thought this video was pretty cool personally!

Very cool! Watching someone else using emacs is always a great learning experience.

I built a platform exactly for this. Check it out here: https://www.nurtch.com/

Wow, it is awesome how you managed to integrate runbooks, Jupyter, and monitoring, well done and great video!

Thanks :)

Just saw that you are CEO of GitLab. Good job making your runbooks public [1]. I converted one of your runbook into an executable notebook to convey my point. Check the before/after screenshot here: https://blog.amirathi.com/2018/03/27/codify-infra-runbooks-w...

You should consider using Nurtch :)

[1]https://gitlab.com/gitlab-com/runbooks

Native Jupyter has the magic %%bash command, so a lot of this should just be possible, i.e. you start a cell with that, and it will invoke bash to execute it.

More generally, there is %%script <x>, which executes the cell using <x>.

0: http://ipython.readthedocs.io/en/stable/interactive/magics.h...

Yep! We've been experimenting with a variant for security & fraud investigations at Graphistry. Our original experiments with just notebooks resulted in a few people on super early adopter teams getting a kick out of it, but in critical ~operational settings, having to deal with code was... not great. Mostly looked like siloed personal use.

BUT. The core concept is great. We made a form more focused on interactive investigation, so you can jump from an alert in a dashboard into a rich & interactive visual session with pre-wrangled data: https://youtu.be/B3ZZWx9WUEk?t=1m32s . Depending on what you see, can easily pull in more data, or refine what's there. And agreed, I think it'd be fun to try in big devops/netops scenarios!

The R community has a really nice answer for this: https://rmarkdown.rstudio.com/flexdashboard/

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