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Performance Collection Rules

更新日期: 2010年7月

適用於: System Center Operations Manager 2007

Performance data can be collected in System Center Operations Manager 2007 from any of the data sources detailed in the Performance Data section of this guide. This section provides the details required for specifying the source of the data and the properties available for specifying the criteria for the data to be collected.

Script Based Performance Collection

Script based performance collection runs a monitoring script on a regular schedule and stores the results as performance data. The monitoring script returns a property bag as described in the Monitoring Scripts section of this guide. The performance collection rule maps values of the property bag into properties of the performance data by using $Data variables referring to different values in the property bag.

Performance data properties that the rule must populate are listed in the following table:

 

Property Description

Object

Name of the performance object. This is typically a static value but may be a $Data variable to retrieve a value from the property bag returned from the script.

Counter

Name of the performance counter. This is typically a static value but may be a $Data variable to retrieve a value from the property bag returned from the script.

Instance

Name of the instance if it is specified. If the target of the rule has a single instance on the agent, the instance name may not be specified. If the target of the rule has multiple instances on the agent, an instance name should be specified by using a $Target variable to retrieve the value of a unique property to identify the target object.

Value

The numeric value to store. This is typically a $Data variable to retrieve a value from the property bag returned from the script.

Optimized Collection

Performance collection rules based on Windows performance counters can be configured to perform optimized collection. Optimized collection reduces the space that is required by only sampling those performance counters that differ significantly from a previously sampled counter.

When optimized collection is specified, a tolerance must be specified that indicates the value that the sampled data must differ from the previously sampled value for the data to be stored. This tolerance can be either an absolute number or a percentage. An absolute tolerance evaluates the difference between the current and the last counter. A percentage tolerance evaluates the difference as a percentage of the previously sampled value.

An example of optimized collection is the Microsoft.Windows.Server.2008.LogicalDisk.FreeMB.Collection rule in the Windows Server 2008 Operating System (Monitoring) management pack. This rule collects the free space in MB on a logical disk every 5 minutes. Free disk space is a value that typically changes gradually, and under most conditions collecting it with this frequency would create an excess number of sampled counters with minimal value. Increasing the frequency of collection though would introduce the chance of missing those periods where a sudden change in the value did occur.

This rule uses optimized collection specifying an absolute value of 100 MB. This means that the counter is sampled every 5 minutes, but the value is only stored if it differs from the last stored value by 100 MB. This still lets it to perform its sampling at a fairly frequent rate but significantly reduces its storage requirements by reducing the number of unnecessary data points.

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