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Decision tree script

IBM Tivoli Monitoring Resource Model Builder automatically generates a decision tree script. The decision tree script contains the information you specified when you created and configured your resource model. If you change one of the settings in the IBM Tivoli Monitoring Resource Model Builder editor panels, the corresponding data, if any, is automatically updated in the script. You cannot modify these settings directly in the script.

The decision tree script contains three basic functions and one subroutine that, by default, produce a return value equal to 0. However, you can specify different values to be returned under specific circumstances.

The decision tree script includes the following default functions:

Main
Created in VBA code (It is created in Javascript, but is not visible when you run a script). VBA requires Main because ActiveX control needs the code to run the script. IBM Tivoli Monitoring Resource Model Builder uses a subroutine to debug the resource model (The IBM Tivoli Monitoring monitoring engine does not call it). This subroutine performs the following actions:
Note:
Do not modify this subroutine. Modifying this subroutine produces unpredictable results.
SetDefaultConfiguration
Initializes the object based on the settings defined in the Events, Thresholds, Parameters, and Actions windows. If you change a setting in these windows, this function updates the corresponding data. You cannot directly change the settings in this function. SetDefaultConfiguration is called only once, when the resource model starts. If necessary, you can write additional initialization code at the end of this function.
Init
Called when the settings defined in SetDefaultConfiguration are replaced with values specified in IBM Tivoli Monitoring profiles. The new values replace the previous settings.
Visit Tree
Contains the monitoring algorithm and is called at the beginning of each cycle. The Visit Tree checks and implements the algorithm. It processes the collected data according to thresholds and parameters settings, and, if necessary, sends an event. You can define the algorithm in such a way that the execution of the data collection is entirely controlled by the algorithm itself. For example, you can run a specific collection based upon the results of a previous collection.

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