MaxAlgorithm

Description

The MaxAlgorithm function smooths raw data within the initial learning time or the continuous learning window by calculating an average over time to find the greatest normal data during the past learning window.

Parameters

continuous-learning-window="<learning-window>"

Specifies how frequently to update baseline calculations when the baseline is in the active state, and how far to look back at data when recalculating the baseline threshold after an agent is restarted.

If an agent is disabled and then re-enabled, the calculation is based on the initial learning time defined by the Baseline function instead.

Default: 1h

For example, if the continuous learning window is one hour, and there is 55 minutes of stored data, the MaxAlgorithm function recalculates the baseline used for thresholds after five minutes.

The format for <learning-window> is <number><unit>, where <unit> is one of the following:

Value	Meaning
s	seconds
m	minutes
h	hours
d	days
w	weeks

Example

# algorithm for dynamic Threshold calculation
self.alg = MaxAlgorithm(continuous_learning_window="2h")