Maximize server uptime - memory leak?

Since we stabilized the newly introduced WLI 8.1 application we are now fine tuning the JVM. We are facing some kind of memory leak which forces us to reboot the WLS instances daily.
I'm now asked to identify some strategies how we could let the WLI instances run for longer than 1 day. My goal is 7 days, so that the machines must only be touched once a week. The relevant JVM settings are like this:
-Xms2048m -Xmx2048m -Xmanagement -Djrockit.managementserver.port=30011 -XgcPrio:throughput
I've choosen the "throughput" strategy as we have here a systems which acts asynchronously most of the time (WLI). I have attached two JRA records. The first ("1day") shows a system which has an uptime of now 16 hours. The heap utilization is almost all the time between 90%-100%. Things get worse after a while. In the consequence we are rebooting the server when we see more and more timeout-exceptions in our WLI layer and heavy GC activity ("average time spent in GC")
The other record ("leakdetector") shows a system which is now running for almost 3 hours. Here I connected the memory leak detector. The graph looks a bit better / more balanced. Means, that after 3 hours the avg heap util remains between the margins of 40-50 %. The trend of the bottom margin however clearly indicates an increasing memory footprint.
To understand this in more detail I started using the memory leak analyzer. So far I got no benefit from using the tool, though it looks very impressive. However, when I connect the memory leak analyzer I can observe some strange heap graph changes. I suppose the memory leak detector has some impact onto the GC strategies, doesn't it? My heap graph looks totally different with no leak detector attached. What can be the reason on this?
Also I'm quite a bit confused why the "Growth" indicator always stays at 0 bytes/sec, even when I can see that objects are getting bigger and bigger. What is the secret here?
i appreciate every comment you have on my case,
thanks a lot

You might also look at approaching the problem for a different perspective. Which transactions, requests, components are creating the most amount of memory? What concurrent requests where active when the memory jumped or an OOME was thrown. I have found this approach effective in getting a good idea on where to focus memory diagnostics after ruling of course a resource capacity issue.
The following article discusses the difference between a leak and a capacity problem.
http://www.jinspired.com/products/jxinsight/outofmemoryexceptions.html
Also you should try high level monitoring to see whether there are global patterns in metric data that provides clues. This blog entry shows what is possible with professional performance management tools with visualizations going beyond pie charts and table views.
Beautiful Evidence: Metric Monitoring
http://blog.jinspired.com/?p=33
There are also many low level memory inspection tools on the market that might help quickly navigate the heap and identify the problem though I think the JRA tool has probably most of the same features.
Regards,
William Louth
JXInsight Product Architect
CTO, JInspired
"Java EE tuning, testing, tracing, and monitoring with JXInsight"
http://www.jinspired.com

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    Kind Regards,
    Asim

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