K8S clusters on VMs strike me as odd.

I see the appeal of K8s in dividing raw, stateful hardware to run multiple parallel workloads, but if you're dealing with stateless cloud VMs, why would you need K8S and its overhead when the VM hypervisor already gives you all that functionality?

And if you insist anyway, run a few big VMs rather than many small ones, since K8s overhead is per-node.

> I see the appeal of K8s in dividing raw, stateful hardware to run multiple parallel workloads, but if you're dealing with stateless cloud VMs, why would you need K8S and its overhead when the VM hypervisor already gives you all that functionality?

I think you're not familiar with Kubernetes and what features it provides.

For example, kubernetes supports blue-green deployments and rollbacks, software-defined networks, DNS, node-specific purges and taints, etc. Those are not hypervisor features.

Also, VMs are the primitives of some cloud providers.

It sounds like you heard about how Borg/Kubernetes was used to simplify the task of putting together clusters with COTS hardware and you didn't bothered to learn more about Kubernetes.

Because k8s gives you lots of other things out of the box like easy scaling of apps etc. Harder to do on VM:s where you would either have to dedicate one VM per app (might be a waste of resources) or you have to try and deploy and run multiple apps on multiple VM:s etc.

(For the record I’m not a k8s fanatic. Most of the time a regular VM is better. But a VM isn’t = a kubernetes cluster).

because if you just do a few huge VMs you still have all the problems that k8s solves out of the box. Except now you have to solve them yourself, which will likely end up being a crappier less robust version of kubernetes.

In a large organization their more efficient to run on VMS. You can colocate services that fit together on one machine.

And in reality no one sizes their machines correctly. They always do some handwavey thing like we need 4 cores, but maybe well burst and maybe there will be an outage so lets double it. Now all that utilization can be watched and you can take advantage of over subscription.

The reason to target k8s on cloud vms is that cloud VMs don't subdivide as easily or as cleanly. Managing them is a pain. K8s is an abstraction layer for that - Rather than building whole machine images for each product, you create lighter weight docker images (how light weight is a point of some contention), and you only have to install your logging, monitoring, and etc once.

Your advice about bigger machines is spot on - K8s biggest problem is how relatively heavyweight the kublet is, with memory requirements of roughly half a gig. On a modern 128g server node that's a reasonable overhead, for small companies running a few workloads on 16g nodes it's a cost of doing business, but if you're running 8 or 4g nodes, it looks pretty grim for your utilization.