I need to improve the performance of my application. We have around 140plus 1.1 CMP enterprise baens and 40 stateless session beans. A average form access around 5-8 each. The application has been slowing down ever since it was developed. Any new functionality added leads to slower performance. We strictly follow the MVC architecture and follow the same design pattern. It runs on websphere 5 DB2 8.1. I am confused on how to reduce the high CPU utilization of the application. Should i concentrate on changing Websphere configurations or think of changing the application design, etc. I have no idea how can i improve in either of the two. pls help as i cannot experiment much because of the application size.
The precisejava link above is an excellent link. The only thing I can suggest on top of that is that before making any changes you might want to do a few things:
1) take a measurement of some sort ot use as a performance benchmark. If you tweak the configuration you will then have a baseline to compare to to know if things are getting better or worse.
2) use a tool such as JProbe to understand exactly where the CPU utiilization is occurring. And then focus there.
thanks a lot it is really informative link
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There are many options to consider when tuning WebSphere performance, such as: heap size, thread pool size, turning off explicit GC (in the code), and/or possibly disabling major GC altogether.
Idle session timeout values as well as KeepAlive settings are also important to keep in mind.
One feature people often overlook is that tuning the TCP stack of the OS on which this is running with the timeout and keepalive values is important to minimize lost connections.
Balancing between the right number of JVM clones and memory per JVM can also be very productive; for example, if you have 10GB of memory on the machine, you might want to have 4 JVMs with 2GB each or 8 JVMs with 1GB each, or something in between.
It's a matter of making a list of parameters/settings to modify and going down the list after changing each one and observing the behavior after a test run.