CPU utilization of less than 80% has to be assured for processor sizing. This is crucial to maintaining efficient response times, because the higher the CPU utilization, the longer the queue, and consequently, the longer the response time per request. If the CPU utilization is above 80 percent, queues grow exponentially rather than linearly. This is based on Little’s Law on Queues. Utilization till the Saturation Density Point (SDP), which is 90% or higher utilization, is assumed. This often results in wait to using averages of 10 to 20, meaning the work will wait for the processor 10 to 20 times as long as its service time at the processor. SDP of 75% is taken as default for Mainframe and Application server workloads. Assuming that the server is configured properly, the dynamic content generated decides the processor requirements. This is greatly influenced by the application which makes it difficult to size the processor. The processing requirements for the dynamic generation are to be benchmarked to estimate the number of CPUs and CPU speed necessary to serve the dynamic content. This estimate requires an understanding of the proportion of transactions that will cause dynamic content to be served to allow the average computational effort per hit to be calculated. The JAVA percent of total CPU time can vary for a given workload. It can be influenced by many factors which affect the JAVA execution time and/or the total system time. Some of these factors are processor configurations, software levels including the middleware components and the SDK, and system/subsystem tuning and customization parameters. The JAVA percent values should only be used as a reference.
The length of time for the measurement can be measured in minutes or hours. At a minimum, we would like to get 15 minutes of data after the application has ‘stabilized’. This means if the environment for the application has a start up phase, or if the application needs to ‘ramp up’ its transaction rate, we would like this portion of the measurement completed before we do our analysis.
No comments:
Post a Comment