Easily, just the way Facebook does it except
maybe better, with one consideration -- they
will have to work their way into such work.

Let's see: For such scaling, it has long been
the case that a first-cut quantitative approach
has been theoretical and
empirical network queuing analysis. So, how
many such Facebook scaling architects are
able to do such analysis, either theoretically
or empirically? I'll bet, not many. Net,
I doubt that the Facebook scaling architects
have a very good approach to the problem.

What are they doing? They have a good
grasp of the basic issues of the components,
that is, the server hard/software, NICs,
LAN switches, TCP/IP stack details,
Linux thread switching performance, etc.
Then they concentrate on the bottlenecks,
solve those empirically one at a time,
and otherwise just f'get about the rest.
Right? I mean, what the heck else are
they going to do, dig into the Poisson
process hypotheses and the renewal theorem?
I doubt it.

So, sure, a humanities major won't come
knowing all about the time/date stamps
on Linux files or about file locking.
That may be stuff they have to learn.

So, for more, need people who can learn
stuff, find materials for the learning,
work with people for the learning,
use some critical thinking about the
material and how to use it.

Then for implementing the results of the
analysis, have to involve other people,
in software, hardware, cable pulling,
HVAC, electrical power, ..., lots of
other people. So, now have to work
with people -- with technical papers,
planning documents, foil decks, presentations,
meetings small to large, one on one discussions,
etc. So, have work with egos, power
struggles, turf battles, office romances,
human nature, etc., i.e., the stuff
nerds ignored (I'm an expert nerd)
in high school, college, and beyond.
The Heine-Borel theorem, fine;
human nature, f'get about it.

So, after I saw Branson's remark, I happened
to visit the Web site of my college
and, there, saw some of the undergraduate
students they were proud of. I doubt
that any of those students knew anything
about Linux internals, but one of the
students in just her extracurricular
activities has organized nearly everything
on campus short of the birds in the trees.
Give her a couple of years, starting as
I outlined, yes with her able to learn
about time stamps on files, etc.,
and when it's time to scale
the Web site, along with moving it to
a colo or our own building, I'd bet she'd
knock the socks off nearly all nerds,
including me. And, if really need some
good work, say, in queuing, bet she'd
blow away the self-taught Linux hackers
who started with C++ in middle school;
for one, she'd be smart enough and good
enough to pick a good consultant in,
say, computer and network performance
at a computer science department and
make good use of some consulting.

Again, I bet that so far the Linux
performance details remain nearly all
fairly simple conceptually. Yes, good
thread switching likely remains a
challenge, but that's quite specialized
work for which draw the larger lessons
from specialists.

I'll provide an example: I was working
in artificial intelligence (AI). We developed
an AI language and did joint work with
MET LIFE and GM and gave a paper at
an AAAI IAAI conference at Stanford.

My wife wanted to learn some of this
material. So I gave her a lecture of
about 15 minutes on how to connect to
the server and use it and then another
15 minutes on our AI language. She then
took two weeks and wrote a nice, first
AI program. Right: BAM, with next to
no background in programming. I looked
at her program and said, "It's a program.
It works. It does what you wanted.
There's nothing fundamentally wrong with
it. But 'AI' has a 'belief', a 'theme',
maybe just a 'hope', and you didn't really
illustrate that ...." So, building on
some of what she'd studied as an
undergraduate, I explained the 'dreams'
of the MIT 'school' of AI. She smiled.
Two weeks later she had a really nice
first AI program. "Nice"? Our project
had as programmers some of the brightest
computer science students in the country,
who were taking computing and AI very
seriously, and they had written first,
sample programs. Her program was several
notches better, the best first AI program
our group ever saw. She did that work
with all of about 45 minutes of instruction
from me and four weeks of time.

Of course, she was 'cheating': She
was brilliant, not just a little but
the real thing. Yes, high school
Valedictorian and in college PBK,
'Summa Cum Laude', Woodrow Wilson,
NSF, etc. She got her Ph.D. in
essentially mathematical sociology
from one of the world's best
research universities and where two
of her professors became President
of the American Sociological Association.
Did I mention she was brilliant?

This detailed computer stuff can be
picked up, fairly quickly, especially
if it is well presented. Good students
can be darned good at picking up such
stuff, including from some horribly
badly written documentation, e.g., as
in the computer industry.

I'm guessing that maybe Branson had
a point. That is, it may be better to
get good smarts, ability to learn,
especially from poorly organized materials,
really good at the '3Rs',
and really good working with groups of
people and just pick up over, say,
two years, what need to know about
a growing server farm based on Windows
Server and SQL Server and my software
(a particular, just one, growing
server farm, not all possible growing
server farms)
instead of hiring for Windows Server,
etc. right away. Maybe.

I'm not fixed in my view but wondering.

Where am I right/wrong?