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These are the detailed results from Michigan's stress-testing of the chat2 tool. The last six weeks have seen some exciting developments from Charles Hedrick and Dave Haines in regards to this tool. We have seen some production performance issues specifically related to the chat tool. The recent performance upgrades go a long way towards addressing these issues.

The current sakai 2.4 chat2 tool appears to execute SQL in the database long after user's sessions have ended. The current build is also very CPU intensive on the database throughout a chat session. The recent patch alleviates the first problem entirely, and diminishes database CPU activity a great deal.

Our test scenario uses a number of sakai tools at regular usage levels. Rwiki, forums, gradebook, resources, dropbox, messages, syllabus, assignments, discussion, schedule, and announcements are all exercised to some extent. We also have two scripts that exercise chat. The first logs on to one of several thousand sites, sends 4 chat messages over the course of 90 seconds, and logs off. The second performs the same steps, but emulates 50 users doing this in a single site. This situation of many users logged into a single site, mostly listening but occasionally sending messages, has been the cause of performance issues here at Michigan. It is this second script that highlights the difference is chat performance.

Bear in mind that 95 seconds of "wait" time is hard-coded in our chat script, so total script response time will never be faster than 95 seconds. Also note that in addition to this wait time, total script response time includes time to log on, select a course, open the chat room, send 4 messages, and log out.

Our test runs for 70 minutes. One of the interesting data points from the previous build was the number of database SQL executions that occurred after the test was finished. Here is the graph of execution count for the current 2.4 production build, and here is the graph for the patched build. Notice the gradual taper off of database executions in the production build, whereas database activity end immediately in the patched build.

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