I'm betting it's moreso that teaching developers to write software that tolerates draining properly (or is even able to communicate draining) is too difficult for them so they work around it.
How many individual teams had software running on your hosts? How many those hosts were stateful, and were fragmented across hundreds or thousands of service groups that had their own fault tolerances and unknown (to infra team) warm-up times. Adding complexity (rolling reboots) to already complex systems is almost never a good idea - at some point, there will be an issue caused by hosts rebooted in the wrong order, or too many hosts of a certain type 2-dependency-levels down being simultaneously offline
> hosts rebooted in the wrong order
Order doesn't matter. Host groups set a threshold for unavailability. Hosts are not rolled unless availability targets are maintainable. Usually this just means the oldest host at any time will get rolled.
Facebook obviously uses hot patching kernel updates to work around a social issue. Instead if you are functionally able to prescribe a set of behaviors that teams must comply to, you can easily do things like rebooting the fleet monthly without impacting availability regardless of the statefulness or fault tolerances.
If I shoot a random host in your pool and it matters to you then you haven't achieved fault tolerance. I'm obviously not proposing shooting an unfair number of hosts to you.
That was not my intention - I genuinely would have appreciated answers to my questions as it be useful to compare the complexity of your setup versus Facebook. As an extreme case: million homogenous, stateless hosts are far less complex to manage compared a million heterogeneous, stateful ones, and very little translates from the former to the latter - in my experience.
> Facebook obviously uses hot patching kernel updates to work around a social issue.
Which I think is reasonable when you have tens of thousands of SDEs.
> I'm obviously not proposing shooting an unfair number of hosts to you.
I agree with you, but I'll go on to say "not shooting an unfair number of hosts" is a hard problem to solve at scale, unless you're willing to make it simple and make humans deal with it by continually draining/undraining services which costs a lot of money without increasing the top line, likely far more money than it cost to get a handful of engineers to write kernel splicing. So beyond it being possibly a social issue, it may be a cost/host utilization issue as well
Even if you can splice there are benefits to limiting uptime, with maintenance reaping the majority.
That's a very realistic/optimistic number (especially as you do want to wait for all services to be running and marked as healthy)
"Oh but you can batch this" sure, but you don't want too much of a big batch that will make your service slow or want to risk shooting yourself in the foot - like rebooting your whole control plane then figuring out it doesn't work like that
(The 45 days is probably an estimate as well, I'm not sure they actually do that server by server)
Taking 45 days is probably more about caution and resolving issues systematically rather than pushing a big button and hoping you don’t cause issues.
I’d expect them to have thousands of microservices - and you only have to find a way to break one to cause big issues.
I wouldn't expect it to be halved by optimization. I'd expect it to be an order of magnitude faster and take more like 4.5 days.
I wouldn't be surprised (but I would be impressed) if they tried and got it down to a full cycle requiring one working day. That's around 1% of hosts cycling every five minutes.