> Broadly speaking, managing 100 "cloud" servers is roughly the same amount of work as managing 2

If this was the case, my billable hours when I was doing contracting would be about 1/10th of what they were. I lived very comfortably of troubleshooting for teams who had gotten themselves into a thorough mess with this attitude. In fact, I earned more from the teams who insisted on cloud setups because they rarely understood the operational issues with it, whereas teams who chose dedicated servers generally thought about operational concerns more.

> Moving from 1 server to 2 is an architecture problem.

Moving from 1 container to 2 is an architecture problem.

Moving from 1 server to 2 running those containers is an architecture problem with well established known solutions.

E.g. for starters you're assuming no containers. But putting the application in containers and leaving the host OS only for basic infrastructure setup is basic practice today if you're running your own servers.

Once you've set up a network boot source (tftp etc.) to network boot of an installer with a suitable setup script that you can trigger via IPMI, and a directory service and a basic orchestrator (be it Kubernetes or something else) on your network, it doesn't matter much if you have 1 server or a 100 - they come up and you put containers on them, and they look no different than a cloud service to the devs.

You're right that it's easier to take shortcuts if you have just a few servers, but it's just as easy to take shortcuts with just a few cloud instances - the number of pet containers I've seen over the years is terrifying.

> The last thing you want to find out is that someone ssh'ed in and installed a package that's required for your service to run

Which is why you don't provide ssh access to the host servers to anyone without an understanding of ops concerns, log everything, and do all updates via an automated setup of your preference, and why you regularly recycle the containers whether you run a cloud environment or dedicated servers.

The reality is that cloud systems do not at all make you immune to this - I've done year long projects to regularise AWS setups that were full of undocumented manual changes to bring everything into a terraform config for example. Often they're worse, because there are a whole lot of unobvious places to look for extra bits and pieces.

> and if you're running a big old monolith, you likely need > 1 instance for some sort of redundancy anyway.

Nobody here suggested a monolith. Nobody is suggesting you forgo redundancy. The. The point of this is that often you can put clear upper limits on the computation you will need to do for either your system as a whole or for a given subsystem, and you can guarantee that you will never need more than one server for a given part of the system.

E.g. a real example: I've worked on a system that did some processing of data about companies. We know this will always fit on a single system because the population growth of humanity is slower than the performance growth of a server and the total number of companies worldwide fits on a single system with several magnitudes to spare today, and the type of companies we were interested in is just a subset. At this point, if you architect a system like that on the basis of assuming you will need to resize, you will risk making choices that makes you far more likely to have to resize. E.g. all of the data I'm talking about can easily fit in RAM on a relatively moderate server now and forever, but the moment you start planning for partitioning the data you have added orders of magnitude of performance overhead for communication.

Properly assessing which parts of a system needs to be able to scale is at the core of architecture, and architects (or devs; it's terrifying how many places lack anyone with architecture experience) who are just planning for infinite scalability for everything is huge red flag to me. It usually means they don't understand their system. For a startup, especially, this is an existential question - preparing for unnecessary scaling has killed many startups.