Usually they go hand in hand.
By the time I left, the developers didn't really know anything about how the underlying infrastructure worked. They wrote their Dockerfiles, a tiny little file to declare their deployment needs, and then they opened a platform webpage to watch the full lifecycle.
If you're a single service shop, then yeah, put Docker Compose on it and run an Ansible playbook via GitHub Actions. Done. But for a larger org moving off cloud to bare-metal, I really couldn't see not having k8s there to help buffer some of the pain.
I agree that Kubernetes can help simplify the deployment model for large organizations with a mature DevOps team. It is also a model that many organizations share, and so you can hire for talent already familiar with it. But it's not the only viable deployment model, and it's very possible to build a deployment system that behaves similarly without bringing in Kubernetes. Yes, including automatic preview deployments. This doesn't mean I'm provided a VM and told to figure it out. There are still paved-path deployment patterns.
As a developer, I do need to understand the environment my code runs in, whether it is bare-metal, Kubernetes, Docker Swarm, or a single-node Docker host. It impacts how config is deployed and how services communicate with each other. The fact that developers wrote Dockerfiles is proof that they needed to understand the environment. This is purely a tradeoff (abstracting one system, but now you need to learn a new one.)
Also, those simpler deployments usually burn more money per utilized compute, or involve reinventing 80% of kids, often badly
It's up to the individual to choose how much knowledge they want to trade away for convenience. All the containers are just forms of that trade.
You surely meant "much less efficient than"
There also seems to be confusion about what I meant by "bare-metal." I wasn't intending to refer to the server ownership model, but rather the deployment model where you deploy software directly onto an operating system.