DevOps lost the plot with the Operator model. When it was being widely introduced as THE pattern I was dismayed. These operators abstract entirely complex services like databases behind yaml and custom go services. When going to kubecon i had one guy tell me he collects operators like candy. Answers on Lifecycle management, and inevitable large architectural changes in an ever changing operator landscape was handwaved away with series of staging and development clusters. This adds so much cost.. Fundamentally the issue is the abstractions being too much and entirely on the DevOps side of the "shared responsibility model". Taking an RDBMS from AWS of Azure is so vastly superior to taking all that responsibility yourself in the cluster.. Meanwhile (being a bit of an infrastructure snob) I run Nixos with systemd oci containers at home. With AI this is the easiest to maintain ever.

Those managed databases from the big cloud providers have even more machinery and operator patterns behind them to keep them up and running. The fact that it's hidden away is what you like. So the comparison makes no sense.