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Servers, DataServers, Messengers, and Adapters
Analyzing OpenEdge Application Performance : Planning an application performance review : Initial investigation
 

Initial investigation

The first question the administrator asks is: "What's changed in my production environment that is causing poor performance?" To begin solving this performance problem, the administrator starts to list the possibilities, as shown in the following table. Note the blank, first column in the table. As each possibility is reviewed, the administrator can use this table as a checklist to identify the items requiring further consideration.
Table 49. Initial investigative checklist
Access and review . . .
As these topics relate to these questions . . .
High-level performance indicators
Have users been complaining about other performance issues that might be related to this performance problem?Are any background processes running during these offending times that could be causing program delays?
Hardware and/or software component changes
Have there been any changes to the hardware or software installations that might have impacted the application's performance? For example, has a new disk been added, or a software upgrade been performed in the time period during which problems have been noticed and reported?
Possible workload changes
Is it possible that some or all of the application inefficiencies noted are related to the number of users working on the application, causing the delays as noted?
Data details in the log files such as the database logs, AppServer log files, customized log files and so forth
Are there any details in the log file data from the time period in which the application was performing poorly that might indicate an application performance problem?
The database performance for possible database issues
Does the database need to be tuned? A tuning effort of this kind can provide significant payoff in performance if it is found to be a contributing factor.
Data from the OpenEdge Management Trend Database from the troublesome time period
By running reports at different time periods, is it possible to see any patterns in the data or reported application responsiveness that match experiences that the users have reported?