I don't know why many people think that they need to be at datacenter scale computing to benefit from abstractions like Mesos, it's completely wrong imo.
It's quite a big shift in mindset but it makes the life of everyone (dev and ops) so much easier when you stop having to think about single machines.
My next startup will be built on Mesosphere. Faster time to MVP and no "go dark for 18 months" when I have to scale.
That number does not seem particularly impressive, if it is accurate. Even "traditional" well-run enterprise IT organizations are often in the 1 admin/SRE to 600-ish machines, so I have a hard time seeing that Google can only do ~2x as good at their scale and with their level of focus.
1 SRE to 5k machines, 10k machines, that makes more sense to me.
Admittedly, I probably have a bad impression of enterprise from consulting because who would pay for automation consulting at $$$ / hr when you do it pretty well with existing resources in the first place?
It seems much easier in my opinion to scale a single function (search or tweet) than the kinds of tasks that a healthcare company has to do like say...scanning faxes from doctors, applying OCR and properly placing them into a pharmacy order system.
you can take a snapshot and say you are 1:n because today you have so many sre and so many machines, but it is very unlikely to be the same ratio down the road.
When you remove the VM smokescreen and count physical boxes it's more like 1 person/100 machines, which is abysmal. I've seen order-of-magnitude people efficiency increases with automation like we're discussing here.
Google SREs by last count were 1 engineer to 1000 machines. In 10 years the common devops engineer at a 200 person startup will leverage the same number of resources using layers of abstraction like Mesos and Kubernetes.