Performance Counter Data Analysis
Analyzing performance counter data consists of examining counter values that are reported while your system is performing various operations. During this analysis you could determine which processes are most active and which programs or threads, if any, are monopolizing a resource. Using this type of performance data analysis, you can understand how your system is responding to workload demands.
As a result of this analysis, you might find that your system performs satisfactorily at times and unsatisfactorily at others. Depending on the causes of these variations and the degree of difference, you might choose to take corrective action or to accept these variations and delay tuning or upgrading resources to a later time.
The level of system performance that you consider acceptable when your system is handling a typical workload and running all required services is its baseline. The baseline performance is a subjective standard that the administrator determines based on the work environment. It might correspond to a range of counter values, including some that are temporarily unacceptable, but which generally indicate the best possible performance under the administrator's specific conditions.
Determining Acceptable Values for Counters
A large set of factors determines the normal operating range for each counter in a typical system. You must drive your system through a large number of conditions and develop a sense for normal operating ranges for your equipment. You should record these typical values in log files for future reference. Then, as you make changes to your workload or your hardware, you can refer to your earlier experience as a baseline.
In general, deciding whether or not performance values are acceptable is a subjective judgment that varies significantly with variations in user environments. The values you establish as the baseline for your organization are the best basis for comparison. You should stress test your applications before releasing them and determine the performance thresholds that cause problems. After releasing the application to a live site, you can monitor the performance and take appropriate action if these thresholds are reached.