With a bunch of hand crafted, hairy code to link the necessary features like fail over, backups, PITR, clustering.

I know, I did all of that.

Which is why I punt that effort to a k8s operator these days, because at the end of the day it does everything I did manually plus makes it easier for me to spin a new database that has WAL shipping and backups to different location.

If you're punting to an operator why k8s? There are lots of managed database providers and if they're managing it, then k8s (or not) is an implementation detail for them to worry about.

Lots of various reasons. Performance, cost, compliance, and reliability are the ones I've personally seen.

These are each specific DB-as-a-services. Instead of sinking my time into learning something universal & competent & capable at many things (Kubernetes) now I'm investing in learning & using a niche service, that I won't have fine control over & whose limits might only be clear down the road. That's a risk.

Sure the dbaas might have superb autoscing and reliability. It may or may not have good OpenTofu/terraform providers available, or other custom niche deployment tools one would need to pick up & adapt.

Same questions as roughing it hacking together pg yourself, except now you have no power. Is observability going to be up to snuff? When performance problems come, how are you going to feel when you discover that analyst techniques a and b work fine but c and d can't be done because you are on managed service that doesn't actually give you full access to the db?

Costs can also add up, and are hard to predict. If you have a managed service, you'll be using a lot more network, which often has some cost (also some latency too). This isn't for everyone, but Kube makes it easy to start with anything (ex: RPi) and scale out. Works with hosted hardware with some local SSD, or I can get a 16-core 7950X and a bunch of gen 5 nvme drives and a fraction of a terabyte of ram for <$2000 and that'll scale me to godlike levels. Whereas I'll keep paying for something hosted.

I think it's so so ideal to have a reliably capable universal autonomic computing later underfoot. Most of the backend has had special specific answers to each question, each problem. We have been disjointed. Kubernetes provides a platform applicable to a vast range of workloads, where yes you need to tune and build different clusters for different workloads, but where the skills transfer much more readily. Everyone in Kubernetes knows how to ship resources definitions/manifests, and that base knowledge is all you need to learn to start consuming services - any services - on Kubernetes. Skill transfer is immediate. Having universal patterns (the API server), backed by autonomic operators making & keeping these resources real: it's so much better than the thousand different paths road of technology we've been on until now.

Because I'm not interested killing both performance (connecting to database over open internet), my opex (hello cloud bills!), and violating customer trust (one of the reasons they pay me is because they do not want to trust American cloud vendors), just so I can have slightly smaller complexity.