PMI Request Metrics
Request Metrics is a tool that allows you to track individual transactions, recording the processing time in each of the major WAS components. The information tracked may either be saved to log files for later retrieval and analysis, be sent to ARM Agents, or both. Request Metrics is different from PMI instrumentation in that PMI provides the aggregation and averages across all the transactions (such as average servlet response time across transaction A, B, and C), while Request Metrics provides response time for each individual transaction (such as the servlet response time for transaction A.)
As a transaction flows through the system, Request Metrics tracks on additional information so that the log records from each component can be correlated, building up a complete picture of that transaction. The result looks similar to the following:
HTTP request /trade/scenario -----------------------------> 172 msServlet/trade/scenario -------------------------- -> 130 msEJB TradeEJB.getAccountData --> 38 msJDBC select -> 7 msThis transaction flow with associated response times can help users target performance problem areas and debug resource constraint problems. For example, the flow can help determine if a transaction is spending most of its time in the Web server plug-in, the Web container, the enterprise bean container or the backend database. The response time collected for each level includes the time spent at that level and the time spent in the lower levels. In the example above, the response time for the servlet, which is 130 milliseconds, also includes 38 milliseconds from the EJB and JDBC. Therefore, 92 ms can be attributed to the servlet process.
Request Metrics tracks the response time for a desired transaction. For example, tools can inject synthetic transactions. Request Metrics can then track the response time within the WebSphere environment for those transactions. A synthetic transaction is one that is injected into the system by administrators in order to proactively test the performance of the system. This information can help administrators tune the performance of the Website and take corrective actions should they be needed. Thus, the information provided by Request Metrics might be used as an alert mechanism to detect when the performance of particular request type goes beyond acceptable thresholds. The filtering mechanism within Request Metrics may be used to focus on the specific synthetic transactions and can help optimize performance in this scenario.
Three types of filters are supported:
Originator IP filter
URI filter
EJB method name filter When filtering is enabled, only requests matching the filter generate request metrics data, create log records, and/or call the ARM interfaces. This allows work to be injected into a running system (specifically to generate trace information) to evaluate the performance of specific types of requests in the context of normal load, ignoring requests from other sources that might be hitting the system.
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