And depending on the problem set in question, one can also potentially leverage "the cloud" for the big bursty compute needs and have the cheap colo for the day to day stuff.

For instance, in a past life the team I worked on needed to run some big ML jobs while having most things on extremely cheap colo infra. Extract the datasets, upload the extracted and well-formatted data to $cloud_provider, have VPN connectivity for the small amount of other database traffic, and we can burst to have whatever compute needed to get the computations done really quick. Copy the results artifact back down, deploy to cheap boxes back at the datacenter to host for clients stupid-cheap.

This is usually not the case because DevOps are often people that mostly worked on cloud services and Kubernetes clusters and not real hardware since most companies do not have on premise hardware anymore.