The Art of Monitoring

Post by peterstjohn » Sun, Jun 12, 2016, 2:23 AM UTC

graycat wrote: post #35

ch wrote: post #32

Earlier quoted context omitted.

I could be bothered. When you say you have a paper, is that something yet to be published? Or is it just sitting in some dusty corner of the Internet?

It was published, in the Elsevier journal 'Information Sciences' in 1999. It appears to be the first, and the first large, collection of statistical hypothesis tests that are both multi-dimensional and distribution-free. I try to be anonymous here at HN, but I'm willing enough to send a PDF of the paper to anyone who wants a copy. E.g., ask for a copy and leave your e-mail address on your HN profile, at least tempora…

Post by reader_1000 » Sun, Jun 12, 2016, 8:22 AM UTC

bogomipz wrote: post #46

reader_1000 wrote: post #33

Earlier quoted context omitted.

There is also icinga2. So how does one decide which one to use? For a mixed environment (windows, linux, etc) which monitoring tool is better when both server and client is considered?

IMHO Icinga 2 is also way too many moving parts. For mixed environments, you should be able to run both Prometheus and Bosun: https://prometheus.io/download/ https://bosun.org/downloads

Post by pramodbiligiri » Sun, Jun 12, 2016, 11:40 PM UTC

graycat wrote: post #16

The monitoring considered in the OP is for server farms and networks where the main challenges are rates of false alarms and rates of missed detections. The challenge is to find means of monitoring that will permit selecting the rate of false alarms are willing to tolerate and, then, for that rate, get the lowest rate possible for missed detections. Thus, would like to use the Neyman-Pearson result. Usually, however,…

Post by graycat » Mon, Jun 13, 2016, 1:17 AM UTC

patrec wrote: post #48

graycat wrote: post #35

Earlier quoted context omitted.

It was published, in the Elsevier journal 'Information Sciences' in 1999. It appears to be the first, and the first large, collection of statistical hypothesis tests that are both multi-dimensional and distribution-free. I try to be anonymous here at HN, but I'm willing enough to send a PDF of the paper to anyone who wants a copy. E.g., ask for a copy and leave your e-mail address on your HN profile, at least tempora…

I'm interested as well.

Post by twoodall » Mon, Jun 13, 2016, 6:29 PM UTC

laichzeit0 wrote: post #45

graycat wrote: post #35

Earlier quoted context omitted.

It was published, in the Elsevier journal 'Information Sciences' in 1999. It appears to be the first, and the first large, collection of statistical hypothesis tests that are both multi-dimensional and distribution-free. I try to be anonymous here at HN, but I'm willing enough to send a PDF of the paper to anyone who wants a copy. E.g., ask for a copy and leave your e-mail address on your HN profile, at least tempora…

So I think the mathematics to make this work is not the problem. How do you engineer this though? If I were to try and build a platform that could do this in real-time for, lets say, a million metrics per minute, can you engineer something that would scale horizontally to do this? Can it be done by cobbling together various open-source tools/libraries currently out there? Then how would you present the results in a w…