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.