[OTDev] OpenAM performance
Vedrin Jeliazkov vedrin.jeliazkov at gmail.comMon Jul 11 12:11:12 CEST 2011
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Hi Nina, Andreas, All, I've switched again the test setup -- OpenDJ runs currently in a separate JVM instance and OpenAM is configured to use it both for user and config data store. I've retrieved the policies owned by nina (1482 policies) and guest (11046 policies) that are defined in the production AA server and imported them into the test instance. I've run stress-testing on this setup which included: -- continuous auth+policy creation+authz+policy removal; -- continuous auth+policy creation+authz; -- continuous auth+authz; Both JVMs are configured with a large heap size (6GB) in order to check how much their memory footprint would grow and minimise the impact of garbage collection on the statistics. After 12 hours of stress testing the JVM that is running tomcat (ambit2+openam+pol) has allocated 2.2 GB, while the JVM running OpenDJ -- 1.7 GB. The main issue we're facing currently is the constant increase of policy creation/deletion latency: http://ambit.uni-plovdiv.bg/cgi-bin/smokeping.cgi?target=IDEA-DEV.AA.TestWorkflow-1a This seems to be triggered by running bulk policy deletions, but has an impact on policy creation latency as well: http://ambit.uni-plovdiv.bg/cgi-bin/smokeping.cgi?target=IDEA-DEV.AA.TestWorkflow-2 Authentication and authorisation are not affected by this problem (their latency stays more or less constant at 20 ms): http://ambit.uni-plovdiv.bg/cgi-bin/smokeping.cgi?target=IDEA-DEV.AA.TestWorkflow-3a The observed slow down might have something to do with the SynchronizedMap which is used by OpenAM to hold the policy modifications. In a thread dump I've noticed that one thread performing policy deletion has acquired a lock on this SynchronizedMap and there were a bunch of other threads waiting for acquiring a lock on the same data structure. This certainly reduces the overall throughput of policy modifications, but it is not clear why the throughput is not constant and the latency grows for a constant workload. Kind regards, Vedrin
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