[CMCDragonkai]

Nix is a programming language/system for software packaging. Along the way, it turns out OS configuration is also just packaging... As long as you don't have anything too dynamic.

It is the most sophisticated programming language/system for software packaging on the market today.

We use it for all our reproducible software development environments. All of our project templates. And all of our employees are issued NixOS configurations so everybody on the team has the same NixOS, the same Nix package overlay... Etc. This level of consistency ensures that we get a level of reproducibility from hardware to OS to user profile to development environment to CI/CD that just doesn't exist anywhere else atm.

It's not entirely perfect but that's not really Nix's fault. It's actually the fault of the rest of the software industry that persists with bad tech. All of Nix's complexity stems from having to package everybody else's mess. Anyway one day I hope the CI/CD systems in the world will just provide Nix jobs directly instead of proxying through a docker container image that I have to setup atm.

[benreesman]

Your shop sounds pretty ahead of the curve. “It works on my box!” “What do you know, mine too!” “Production person over here: I’m getting the same thing!”

It seems to me that people who go through the agony and ecstasy of getting it set up do so because the difficulty of the domain is high and the headcount is low: you need leverage in that setting.

Can you share anything about what motivated your group to get it dialed in?

[CMCDragonkai]

My company matrix.ai was working a new cloud orchestration platform and Nix was core to how customers would package their applications/containers for deployment. The OS development is halted for now while we are working on a secrets management system.

So it was only natural to fully dog food Nix. We also introduced it to clients during our computer vision machine learning consulting work. It was the only way to get reproducible projects involving a complex set of Python dependencies, Tensorflow, CUDNN, CUDA, Nvidia libraries (there is a very strict set of requirements going all the way to hardware). I actually first tried doing it with Ubuntu and apt, it did not work. Setting up your own nixpkgs overlay is a must in these scenarios.

It is definitely something that is easier to fully dial in when you start from scratch. It's a comprehensive system so it will take time for adoption. I always recommend starting with it as a development environment tool first, then consider automating your OS conf or user profile or VMs... etc.

[mvoodarla]

What was the orchestration system used for? Was it in the case where there were many models that needed to be run one after another. I know it's a huge problem in video processing to be able to increase speed a ton. My company Sieve (see profile) is building infrastructure specifically for running ML models on video which is why I'm curious.

[CMCDragonkai]

It was built for AI driven container orchestration, configuration synthesis from high level constraints.

Yes ML workloads is particularly complex, because they have both batch oriented data flows (training), and service oriented data flows (inference). There aren't many systems that can adequately express both.