Forum Discussion

Mahlon_Greene's avatar
7 years ago

DEVIATION FROM ROLLING AVERAGE

I see a need in the design to alert on deviation from rolling average:

example 1:   Temperature in hardware is based on fixed baseline (default or manual adjusted) or based on fixed Delta.

In real world application it would Make a LOT more sense to alert on Deviation from a 5 day or 30 day rolling average Temp of the box.

Reason is,  units alarm on the weekends because the office shuts off the AC during the summer.   or they alert During the week 9-5 because in the winter the offices crank the heat.

All of these ignore nuance of RANGE and Average expectation for the location...The alerting should just be how FAR outside the average Range for the site is.

 

My Nashville facility hovers from 56 to 59 all week.    I have it set on 57 so I get alerts at least once a weekend.

I could move it to 59...but that's a band-aid.   The REAL solution would be to have the software TRACK the last 30 days, and alert when we're outside the NORM for that location.

furthermore....with hardware it is not the specific temps that kill the hardware....its the RATE at which the temp changes.

so, the alerts SHOULD be based on the average range the system has seen in the last 30 days, and alert ONLY when the rate of change accelerates...but I imagine THAT request would be more challenging to reduce to an algorithm.

 

Example 2:   PING times.....I have sites where the Latency range is EXTREME (Mumbai, Johannesburg, Taipei etc...)

I'd wished the PING would track the 30 day range and common deviation from norm and alert when the sites see latency that is way outside the expected fluctuation range.

30ms typical 90% of the time

+

200-500ms spikes 10% of the time.

when Ping times hit 300 ms for more then 10% of the last hour of sampling....then notify warning to inform of change in TREND....not fixed threshold in immediate sample 

1 Reply

Replies have been turned off for this discussion
  • Additional Comparison Methods like @Mahlon Greene suggested against Standard Deviations or other statistical model would be great!