It was done a tested more than once. As I recall, it took quite a bit to get Linux to perform to the level that BSD was performing for (a) this use can and (b) the years of investment Netflix had already put into the BSD systems.
So, could Linux be tweaked and made as performant for _this_ use case. I expect so. The question to be answered is _why_.
Chaos Monkey was explained to me as "The (virtual) monkey swinging around the (virtual) data center unplugging the (virtual) cables". It very well could have been based on Robbins. The point wasn't originality - the point was to have the same benefit in our burgeoning cloud environment.
Initially we wrote the library to help us answer the question about what change may be causing impact to our customers' experiences. Out of the billions of time series metrics we have we knew there were about 10,000 or so likely (for this initial use case), possible candidates and we wanted to reduce that set as far as possible and either (1) find /the/ candidate for problem or (2) produce a short list of things for the humans to look into. In order to get to the point where we could ensure high likelihood of apropos correlations, we needed to do some work on the signals first.
First we detect if any of the possible candidate signals were born or died in the interesting time period. We use these time points to reduce the window we'll use to pass to the correlation functions. We can also detect any changepoints in the time series and apply similar logic. Once we've determined the best window bounds for each candidate signal, we use pearson and spearman correlation functions to get a score for the pair of signals -- the initial signal that started the inquiry and the candidate signal using the determined time window.
The code is about 98% data preparation, signal analysis, and window determination and about 2% correlation work.
(I've tried to summarize quite a bit, let me know if you'd like clarifications or have other questions.)
In my opinion, it doesn't count unless its in production.
Why? Your customers use your production environment, not your test environment. Something will cause loss of an instance for you:
* Mistaken termination
* AWS retirement (and you missed the email)
* Cable trip in the data center
* <Something else we can come up with>
* <This list goes on>
So, vaccinate against the loss of an instance cratering your service. Give your prod environment a booster shot (with Chaos Monkey or something like it) every hour of every day. Then, when anything from the above list happens you're infrastructure handles it gracefully and without intervention. Continued booster shots ensure that this stability continues through config changes, software version changes, OS changes, tooling changes, etc.
I think the better question is "Why wouldn't you do this?"
So, could Linux be tweaked and made as performant for _this_ use case. I expect so. The question to be answered is _why_.