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Best Practices for Siebel ARM

Review the following information as recommendations of best practice when converting Siebel ARM files.

• Set the Siebel ARM granularity level to level 1 for monitoring production deployments; set the Siebel ARM granularity to level 2 for diagnostic purposes.
• Set the SARM Max Number of files parameter to 0 in order to disable Siebel ARM file creation. This scenario may be useful when enabling Siebel ARM for use with other third-party ARM tools.
• Make sure the Siebel ARM feature has flushed data to the Siebel ARM file before converting the file. The Siebel ARM feature creates an empty Siebel ARM file before data is flushed to the file. For details on this process, see the descriptions for SARM Data File Size and SARM Period in About Siebel ARM Parameters and Variables.
• Change the value of the SARM Memory Size Limit (alias SARMMaxMemory) or SARM Period (alias SARMPeriod) to a lower setting if the Siebel ARM files remain empty on a consistent basis. For details on this process, see the descriptions for SARM Data File Size and SARM Period in About Siebel ARM Parameters and Variables.
• Make sure the Siebel ARM file name and path name, as necessary, are correct when referencing the Siebel ARM files in the commands.
• Split large Siebel ARM files using the -p flag with the Siebel ARM post-processing tool if the Siebel ARM post-processing tool cannot convert the Siebel ARM file or the output file is too large. For further information on the -p flag, see Table 8.
• Concatenate Siebel ARM files to increase the amount of performance data for a given process. For example, as the Siebel ARM feature can save numerous Siebel ARM binary files for each process, concatenate these files to view performance data for multiple requests for this process. (For details on the number of files saved, see the description for SARM Max Number of Files in About Siebel ARM Parameters and Variables.)

  TIP:   Use a third-party utility to concatenate Siebel ARM files on Windows. Use the command cat list_of_files > filename.sarm to concatenate Siebel ARM files on UNIX.

  NOTE:  Only concatenate Siebel ARM files of the same process.

• Gather performance analysis data on your Siebel application before customizing the application. These baseline measurements provide a good reference when monitoring the performance of your Siebel application after any customizations.
• Run a user session trace analysis if there are performance problems for an individual user during a particular session. The user trace session trace data identifies each request the user made and identifies which request required the longest time when compared to a base line.
• Use the performance aggregation data to diagnose performance at a given point in time or for a certain process. Reviewing the data by group can diagnose the area that is performing poorly. After reviewing a high-level view of the performance data, extrapolate a more detailed review by running the comma-separated value analysis. For details on running this analysis, see Running Siebel ARM Data CSV Conversion.
• Compile performance aggregation data over a period of time to determine a trend analysis.