tl;dr: do you want to be a DBA? do you want to be a cluster admin? If you want to be both you can run databases on Kubernetes. If you don't want to be a DBA, use a managed service.
Non-containerized environments (VMs, bare metal) are well-understood and fairly predictable; Docker and Kubernetes are moving targets. There are "known unknowns".
As an example, I am involved in a project that uses continuous delivery for deploys, and we recently had an incident where the GKE node ran out of inodes because Docker was keeping all the layers of dead containers around. Kubernetes handles this correctly: Best-effort pods were evicted and the node went back to being ready once the inode use went down. PostgreSQL would have stayed up in this case, but it was still a little surprising that GKE, which is nominally managed, does not have a process in place for cleaning up Docker's garbage. (Edit: Apparently it's a bug [1].)
When discussing Docker and Kubernetes, there are very often edge cases that come up. For example, until a couple of months ago, Kubernetes had a serious bug that would often cause the wrong network volume to be mounted to a new pod. You can be the world's best containerized-database admin and still be surprised by things like this, which have nothing to do with the nature of containers, and everything to do with the specifics of the software that controls them.
"containerd is all we wanted from @docker in @kubernetesio and none of what we didn't need: kudos to the team!"
For example, I'd be able to upgrade by just starting another container and replicating into it, then routing traffic over. I'd retain the option of rolling back by routing traffic back if anything goes wrong. I'd be able to spin up/down redundant read-only replicas simply by changing the number of replicas. And other apps would be able to piggyback on Kubernetes' discovery system (typically you let service names resolve into IPs/SRV records through DNS). And so on.
You can do anything you want with classical VMs, of course, it's just more static and slower: Provisioning another VM, configuring it (Puppet, Salt, Chef, etc.), connecting persistent storage, reconfiguring everything to point to the right places, configuring DNS, etc.
In short: If you use Kubernetes as your orchestrator, why would you not want to use it for everything?
But it just seems like you're trying to shove a very stateful management problem (the schema, the associated storage) into a system designed for mostly stateless stuff. And that way lies a giant hassle.
Plus we're certainly not at huge scale, but db rollbacks are nontrivial, and we have to be somewhat careful about schema modifications.
Thanks for your comment!
There's nothing about containers that says they need to be stateless, it's just more convenient that way because you can treat every container as expendable, redundant, fungible commodities. But the real world needs state, and Kubernetes is capable of managing it. In particular, the pattern pretty much required for stateful apps on Kubernetes is that of using an exclusive-access network block device. Since only one container (or pod) can mount it at any given time, you can ensure that the state follows the container around.
It may just be our use case -- we have enough data (low TB) that cloning is not a fast thing to do.
Thanks again!
I've been wary of running anything stateful on K8s for other reasons than the stable identity stuff. Historically, Docker's I/O has not been particularly robust — well, Docker has not been particularly robust. You also have to be very careful about resource limits and requests.
In particular, you have to ensure that the QoS class "Guaranteed" [1] kicks in, because the last thing you want is for Kubernetes to think that PostgreSQL is something that is happily rescheduled.
[1] https://github.com/kubernetes/community/blob/master/contribu...