Glad you liked it :) It turns out that modeling operational metrics is a lot harder than I expected, so there was quite a bit of work we had to do to get the algos to work.
I was wondering about this. I assume you're treating this info as proprietary, but in case you aren't I'd love to hear more about how you actually implement this.
Well, there's a lot of details and I don't think I can cover it all here, but if you're interested in the general framework that I used to approach this problem, take a look at this blog post I wrote last year: https://medium.com/@upal/how-to-use-machine-learning-to-debu.... Let me know if you have any feedback!
I am a little surprised that you got some milage out of procedures and algorithms that rely on the Gaussian assumption (that includes k-means). From experience, the raw metrics are, shall we say, as violently non-Gaussian as it gets. OK OK you need not tell what you are doing to address that as I myself am being rather economical with the truth. But so glad, so glad that someone is using multivariate analysis, about time too. From someone who dabbles in a similar space I wish you well.
Thank you :) Yes, the use of multivariate analysis was a crucial insight for me, and I'm hoping these ideas will push the monitoring community forward!