Regrettably the folks who have been using it for years aren’t going to be give a lot of specifics, but generation of k8s yaml / jsonnet in particular was exceptionally common. One example from the other thread:
> My team migrated several kloc k8s configuration to pkl with great success. Internally we used to write alert definitions in pkl and it would generate configuration for 2 different monitoring tools, a pretty static documentation site and link it all together nicely.
Can't speak to Pkl, but for Jsonnet I made it possible to fully define then load neural network model architectures directly from Jsonnet config files [1], rather than relying on Python's unsafe pickle module.
Since neural networks often have many repeating features, using a traditional configuration language requires repeating the same structures a lot, whereas using Jsonnet you can use `std.repeat` instead. You can see some examples of this in the readme of my package.
I've seen their usecase documentation entry. And I understand the benefits this could have.
But I think I need some hands-on usecases, to fully grasp why or how I would use this.
Thanks