You might be doing it wrong. I use k8s for my personal projects and the maintenance overhead is lighter than what it cost me to log into my VPS every 3 months and renew the Let's Encrypt certificate. (Which was literally just pressing the up arrow and enter, because it was always the last thing in my shell history.) At work, a team of 5 people maintain our production Kubernetes clusters (that host our cloud product and app), and develop the app itself. Which by the way, creates Kubernetes clusters for individual customers, of which we have created thousands of. Overall, it's not that hard and we don't spend much time managing computers. (We do have all of the good stuff, like all K8s changes in Git, one-click deploys, etc. I did spend a little time making Shipit run in Kubernetes, but it certainly wasn't my full time job for any extended period of time.)

There are problems that people run into. One is not needing more than one computer -- if everything you need to run fits on one computer, you might as well use systemd as your orchestrator. (Which people also say is overly complicated, but really it's just extremely misunderstood.) The other is not understanding Kubernetes enough. A lot of people just explode random helm charts into their cluster and are mad that it's hard to maintain. Basically, adding another abstraction layer only helps if you can debug the actual thing on the surface -- otherwise, you're just setting a time bomb for yourself. (And, helm charts require you beg the maintainers for every feature you could possibly need, and once enough people have done that you just have raw k8s manifests where everything is called some random word instead of its actual thing. Really bad. Use Kustomize or jsonnet!)

Compared to something proprietary like AWS ECS, K8s seems like it's almost impenetrable to learn. If you're already on one of the cloud providers, likely they will have something else to offer.

ECS isn't exactly simple either, but it is manageable for small shops where the developer is the devops guy.

it’s not only suitable for google scale problems, rather it isn’t for all problems. Like a lot of new shiny tech, it takes time investment to find out if something really is the solution to a problem. Don’t just jump in with both feet.