kafonek / fastapi_service_example

JupyterHub service written with FastAPI / uvicorn

Hi, I'm @kafonek (Matt Kafonek) 👋

My first career was as a domain expert in the intelligence community. I fell into it as a young enlisted USAF linguist, and kept working in the field for almost twenty years as a geolocation specialist and technical analyst with VaST. I began learning Python around 2010 to help automate some day-to-day tasks. As I shared what I learned with other analysts, using tools like Jupyter, I developed a passion for empowering domain experts. One part of that is providing "no-code" / "low-code" tools, but an underserved need is giving them the right opportunity to begin learning and using code themselves.

My second career as a software engineer started with Noteable, a managed Notebook platform to make data accessible to all. I learned countless valuable lessons developing and deploying features for a production application. Our backend stack was Python (FastAPI) and CockroachDB (async SQLAlchemy), with the Kernel compute orchestrated through a Kubernetes Operator and custom resource definitions. We home-rolled RBAC and real-time synchronization 😬. When ChatGPT announced the plugin store, and later custom GPTs, we were in a unique position to be first-to-market with a Notebook/coding plugin, which landed on the initial "popular" store. I have seen what happens when a startup catches lightning in a bottle, and it is freaking cool.

My current interests are twofold: learning Rust and becoming more comfortable applying practical AI. I am excited about Rust because its syntax, build tools, and ecosystem are approachable. It's also blazing fast and compact. I believe the future of performant Python is Rust. Deploying apps to the browser with web-assembly has a lot of promise, and Rust has a tremendous story there. As far as AI goes, the experience with Noteable was "magical" but we were effectively just interacting with OpenAI APIs, whether it was ChatGPT making calls to us or our app making calls to OpenAI. I'm looking for opportunities to utilize local models, work with multi-modal models, and learn about deploying and optimizing models in production.

Outside of work I spend my time solving programming puzzles, playing video games, rock climbing with my wife, and taking care of our two young boys.