I have recently been re-introduced to Jupyter Notebooks. If you are not familiar with this tool, here is the description from their website:
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
https://jupyter.org
I recently incorporated a Jupyter Notebook into an internal dashboard project I was working on, to give in-depth access to metrics data. We use Instana for our Application Performance Monitoring tool. However, we seem to constantly run into issues with their UI, where they just do not present the data we need. Particularly on infrastructure metrics for “dead” services/processes. Luckily, Instana provides an API for accessing these metrics as well.
I chose the Jupyter Notebook for this problem precisely because you can blend narrative text with live code and visualizations. Most of our developers are not familiar with Instana’s API, so the narrative text helps explain what is going on. On top of that, the live code can’t lie. Developers of course gravitate to these examples. Pulling in nice ways to also chart and visualize the date is just icing on the cake.