ZenPacks.community.PredictiveThreshold

Description

This ZenPack adds a new Predictive Threshold type for determining when to trigger an event. The threshold uses the Holt-Winters Forecasting from RRDTool.

Retrofitting data exists in the Predictive Threshold. It renames the original .rrd with a .old extension. The RemoveHoltData.py script packaged with the ZenPack is a command line tool for converting RRD data back to regular RRD files if you want to convert them back to standard thresholds.

Holt Winters Parameters

Alpha = 0.1 # 0-1 , value closer to 1 means more recent observation carries more weight, baseline

Beta = 0.0035 # 0-1 , value closer to 1 means more recent observation carries more weight, linear trend

Gamma = 0.1 # 0-1 , value closer to 1 means more recent observation carries more weight, seasonal trend

Rows = 1440 # rows >=season, 5days, 300second_intervals * 1440 points

Season = 288 # 1day, 288points * 300second_intervals

Window = 6 # window length .. (eg 6 observations for alerting)

Threshold = 3 # number of periods it has to fail in a window before alert sent

Delta = 2 # of standard deviations away from predicted value (for alerting)

Prediction Color = Color of the predicted value line

Confidence Band Color = Color of the confidence bands placed at delta standard deviations from prediction line

Tick Color = color of vertical line indicating threshold has been crossed at that value

Requirements & Dependencies

Zenoss Versions Supported: 3.0

External Dependencies:

ZenPack Dependencies:

Installation Notes: zenhub and zopectl restart after installing this ZenPack.

Configuration:

Limitations

Beware if you are testing and creating a new template that it takes about 2 days before there is enough data for the Holt-Winters RRA archives to have data so although you see the new lines on the legend of a graph, there are no data lines for this long.

I don't think installing the ZenPack per se, will corrupt anything you currently have; however it may cause problems to existing data. Have a look at http://community.zenoss.org/message/50360#50360 - I have seen this both on the old version with 2.5.2 and with the new. I would take my own backup of RRD files before applying a predictive threshold.

Download

Download the appropriate package for your Zenoss version from the list below.

Zenoss 3.0+ Latest Package for Python 2.6

Installation

Normal Installation (packaged egg)

Copy the downloaded .egg to your Zenoss server and run the following commands as the zenoss user:

zenpack --install <package.egg>
zenhub restart
zopectl restart

Developer Installation (link mode)

If you wish to further develop and possibly contribute back to this ZenPack you should clone the git repository, then install the ZenPack in developer mode:

zenpack --link --install <package>
zenhub restart
zopectl restart

jcurry / zenpacks.community.predictivethreshold Goto Github PK