05-11, 11:30–12:00 (Europe/Paris), Louis Armand 2
Today, Jupyter Notebooks are mostly confined to science, research & education. But notebooks can provide organizations with a powerful general-purpose “executable documentation” platform. A solid use case for this is DevOps & more specifically, IT incident response.
Technology teams usually have an on-call rotation with static wiki-style documentation to guide the on-call engineer. Jupyter Notebooks can replace static documentation with executable notebooks. E.g. “fetch service logs” and “rollback last deployment” can simply mean executing a code cell that’s available alongside the markdown instructions.
What are the benefits of executable vs. static documentation -
- Quick e.g. “check DB latency” is 1-click notebook code cell execution to plot latency graph vs. going to a third-party UI in the middle of an incidence
- Precise e.g. “promote read replica to master” can mean a series of steps & possibility of human error; codifying the steps in advance removes ambiguity & results in precise action.
“Executable documentation” is a simple yet powerful concept that can extend to other use cases such as - API documentation, developer onboarding, data visualization & reporting, scheduling routine tasks & so on. Think of it as executable GoogleDocs powered by Jupyter!
In this talk, we’d like to,
- Introduce the concept of an “executable documentation” platform powered by Jupyter
- Show a demo of how it’d work for IT incident response (https://www.youtube.com/watch?v=vvLXSAHCGF8)
- Talk about important considerations of building an executable documentation platform
- Illustrate other use cases for executable documentation
Amit is a software developer & the founder of ReviewNB, a code review tool for Jupyter Notebooks.
He's a Carnegie Mellon graduate, previously worked at Amazon Music team in Seattle & helped build location stack at HyperTrack.
Amit is a strong proponent of automated testing & code reviews as they help us quickly build reliable software & learn from each other. He's deeply interested in the human side of software engineering- development processes, collaboration tools, and such.
Vinay is currently the Founder and CEO of Abhyasu.com, an ed-tech initiative to teach Python and AI to 10-14 year old kids. Previously, he architected ML Platform at Lyft, co-founded a startup that was acquired by Lyft, built AWS Elasticsearch and CloudSearch services, and built Amazon.com's product search engine.
Vinay holds MS in Computer Science from Stanford University, USA, and BE in Computer Engineering from the College of Engineering, Pune, India.