I run my own temporal service in my k8s cluster; this setup is the backbone for almost all my applications. For simplicity, I opted for the postgres backend. You still need to run the 4 (?) other service (history, matching, frontend, ui, maybe others, definitely others if you want observability with prometheus/grafana, and tad bit more complexity if you want tailscale to get in there and poke around).

They ship Helm charts so reality is somewhere between "helm deploy" and "substantial ops burden". I don't have to touch it very frequently, but that is not to say I don't have to touch it. There's occasional releases and there have been times where (probably due to my inexperience with helm) I botched an upgrade and lost some data. And I've been on this journey for years; when I first started, they didn't have a Python SDK and it was one of my (many) excuses to learn Go. But anyway to your point, yes, if you're comfortable with k8s and Helm then you shouldn't have much of a problem running hundreds of thousands of workflows; if you want to really push the throughput and optimize cost you probably need to get creative the individual services and look into cassandra (maybe? idk).