This is an example of what I mean by "AI Hard". Yes, obviously, rolling updates is an improvement over non-rolling updates at scale. However, you still have th

This is an example of what I mean by "AI Hard". Yes, obviously, rolling updates is an improvement over non-rolling updates at scale. However, you still have things like "this update severs the machine from the management system due to unexpected XYZ", "this update is fine until it's rolled out to 80% of the world, at which point interactions with the other deployed systems hammer the system so hard the management interface can't get in properly", "this update looked fine because it was using almost entirely cached data but once the caches all expired it turned out to be a disaster, now restoring is a nightmare because we had to roll back the version, empty the cache, and regenerate everything", and all the other edge cases that no matter what you do, will cause cascading failures at a huge scale. No matter what rule set you write, something's going to get past it. Or, to put it another way, if you aren't yet on the Pareto frontier between power and safety, sure, by all means go get your free safety and power. But you will hit a limit on the two before you have all the power and all the safety, and the limit you will hit is going to be uncomfortable in at least one direction.