All of this is true, but I'd wager there's 10, at MOST, entities on the planet that are large enough to warrant this level of ... "architectural overkill". The other 99.99% of us don't need it.
I CERTAINLY don't debate that Google, or Amazon, or Facebook, or Netflix, or the phone system, or anything else that touches a noticeable percentage of the human race needs architecture like this to provide "5 9s".
But, just like when "big data" became a buzzword, and many people thought their problem needed "big data" approaches to solve, the thought that all but a small minority of entities need this is Simply Wrong.
I am reminded of a client doing something with genomics about 9 years ago. They had some over-complicated "new tool" infested approach to solve their "big data" problem, but the run times were taking too long. I was brought in as a consultant to improve it. After I was done, a data processing run that took hours (causing employees to run them overnight) before took minutes, or seconds. What did I do? I got rid of all the complexity. I replaced their expensive cluster with one studly provisioned machine. I replaced their collection of networked Java microservices with 1 non-networked multithreaded C program. I replaced their XML based format for data at rest with something I whipped up, tuned to what they actually needed.
Once their "we need big data!" >10TB data set could fit in a single machine's memory, the rest was easy. What used to "require" a cluster of machines and overnight processing could be done interactively, and quickly enough for the scientists to get into a much more productive "flow", doing dozens of runs per day.
tl;dr: unless you're google (or google scale) you don't need all this crap. :)