Random projects of an Engineer, Programmer and Human Enthusiast
The projects below are open source contributions I've made over the years on my own & completely unrelated to anything done at my employer (or past employers). Enjoy!
Hello! If you'd like to reach out, please shoot me an email at: mark(at)kockerbeck(dot)com
This was a project I did to make a basic protobuf RPC style Python service & explore running it in various Docker orchestration systems. I settled on Kubernetes & have committed everything relevant that I needed to get that working.
For whatever reason, this is the most "popular" FOSS project I've ever started. It's just a silly web server utility to show coverage badges from SonarQube. It was fun as I got to setup a bunch of infrastructure & sling some Node with other strangers on the Internet.
This is an implementation of an Elastic Beat that monitors IPv4 routes. I did it during a holiday break & it was a lot of fun. Amazing to see how frequently Google routes change from my location at Cox.
One of the first mobile apps I made & while it was temporarily useful, it grew silly in concept... essentially it's a mobile interface to an etcd cluster to control keys. Mobile development with Xamarin was fun though.
A bit of a hack. I wanted to show people how easy it is to reliably subvert local network security if you have access to nodes inside & outside a given IP space if only 1 communication direction is allowed.
Ok, this is technically the most popular repo I have. A long, long time ago, when this whole "MapReduce" idea was coming about, I conjured up an implementation in C# using extension methods. Utterly useless, apart from learning.
While I was learning Go, I made a presentation to give to my Corporate Applications team. The presentation is run from a Go HTTP server. It was fun, I did it on my own time & thus presenting it on the internet. You can see a live version at: golangfun.epicapp.com
I'm still working on this one. It's an example of how to build TensorFlow Serving components and create containers for training, inference servers and clients. I'm basically just working through the complications from the TensorFlow Serving repository.