There certainly are people with use-cases like that, but it is rare to find people who both have large, sudden spikes that are not better handled in other ways (e.g. combination of CDNs and micro-caching), or where the load can not be trivially smoothed out enough (e.g. there's enough work with relaxed latency requirements or that can be scheduled to off peak times, or where the spikes are not small enough relative to base-load that it still pays off to put most load on dedicated equipment and use AWS or similar to handle spikes only.
People often think they have workloads like that. I've done work on plenty of setups over the years were people were certain they had lots of big spikes, but most of them only had moderate day/night cycles (and usually a lot less spiky than they thought, because they'd never bothered to measure).
Only in a few cases I've seen usage patterns that justified spinning instances up/down very often, and for those cases, ironically the availability of clouds have made dedicated hosting more cost effective, because if you host everything in VMs or containers anyway, you can now get to far higher utilization levels on your on-prem/colocated setups, and be prepared to spin up some cloud instances (automatically, if you wish, it's not that much effort), and tie them into your cluster when your load warrants it. It's not suitable for all workloads, but it works surprisingly well if anything.
I do see that argument a lot for using cloud providers, but the vast majority of cloud setups I've seen end up having very static workloads growing at rates that gives plenty of time to prepare.