[programd]

Let me throw this out as a provocative take:

In the age of AI arguments about a configuration language are moot. Nobody is going to hand craft those deployment configs anymore. The AIs can generate whatever weird syntax the underlying K8s machinery needs and do it more reliably than any human. If not today then probably in 3 months or something.

If you want to dream big for K8s 2.0 let AI parse human intent to generate the deployments and the cluster admin. Call it vibe-config or something. Describe what you want in plain language. A good model will think about the edge cases and ask you some questions to clarify, then generate a config for your review. Or apply it automatically if you're an edgelord ops operator.

Let's face it, modern code generation is already heading mostly in that direction. You're interacting with an AI to create whatever application you have in your imagination. You still have to guide it to not make stupid choices, but you're not going to hand craft every function. Tell the AI "I want 4 pods with anti-affinity, rolling deployment, connected to the existing Postgres pod and autoscaling based on CPU usage. Think hard about any edge cases I missed." and get on with your life. That's where we're heading.

I'm emotionally prepared for the roasting this comment will elicit so go for it. I genuinely want to hear pro and con arguments on this.

[lmm]

All the more reason you need a concise, strict representation of your actual config. If you're trusting an AI to translate fuzzy human intention into a machine protocol, there's less need for fuzzy human affordances in that machine protocol, and you should use one that plays to the strengths of a machine representation - one that's canonical and unambiguous.

[eddythompson80]

If you want to dream big, why not give that post to AI and let it parse it to generate K8s 2.0, then you can get it to generate the application first, then the deployment. You can even have it feature-ask itself in a continuous loop.