This is my experience too. I've used smaller-scale tools (such as docker-compose, Dokku, Heroku etc) but I've found them to be a mixture of unreliable or unsuit

This is my experience too. I've used smaller-scale tools (such as docker-compose, Dokku, Heroku etc) but I've found them to be a mixture of unreliable or unsuitable in the case of fairly modest complexity. Eventually I turned to Kuberenetes to see how it compared. I spent a day-ish reading through the 'core concepts' in the docs which was plenty enough to get me started on GKE. It took me a week or two to migrate our workloads over, and once everything stabilised it has been pretty much fire-and-forget. I have about twenty pieces of software deployed for my current client and I feel that I can trust Kuberenetes to just get on with making everything run. I've since deployed clusters manually (i.e. bare metal), but I certainly wouldn't recommend it for anyone starting-out. Personally I'm keeping a close eye on k3s. I think my main learning during this process – at least for my situation – was to run any critical stateful services outside of Kubernetes (Postgres, message queues, etc). I think this applies less now than it did when I started out (v1.4), but non-the-less it is a choice that is still serving me well.