For developers and operations teams building and managing applications with Microsoft Message Queue (MSMQ), the AppDynamics platform provides a comprehensive solution for monitoring and managing the performance of your .NET applications. With rapid installation and the most scalable architecture in the industry, AppDynamics solutions help you deploy your applications more quickly and with more confidence.
In this example, AppDynamics auto-discovers 2 ASP.NET tiers and 2 backends. MovLib-Web is making an MSMQ call. The flow map shows the communication as the average number of calls per minute made by the tier for an MSMQ call and the average response time for a single call.
AppDynamics takes transaction snapshots which contain diagnostic data to help you quickly analyze and troubleshoot problems with MSMQ and other types of business transactions.
Double click on the transaction snapshot will bring you to the transaction flow map. It show the flow view of the transaction snapshot. In this example MobLib-Web tier is making an MSMQ call which is taking 20ms (1.9%) time.
Drill down into a transaction snapshot to display the call graph. The call graph displays the code execution sequence timing, so you can identify which methods have problems. In this example, The System.Web.Mvc.Controlle:ExecuteCore method is taking 110 milliseconds, 10.3% of the time for the MSMQ call.
MSMQ calls are detected under remote services. This section describes about the type of call, calls/min, response time etc. In this example, there is an MSMQ call with 30 calls/min, 6 ms response time and 148 calls.
Double click on the remoting call will open its dashboard. This dashboard shows the flow map of the MSMQ call. In this example MovLib-Web' tier is making an MSMQ call. The properties are listed on the right hand side of the screenshot.
AppDynamics collects metrics (backend performance MSMQ in this case) of ASP.NET applications. Use the metric browser to create graphs of critical statistics. The graph below shows calls per minute (in green), average response time (in blue) and number of errors per minute (red). In this example the average response time was maximum at 2:32am, there were no errors found and the average response time was greater than the calls/min between 2:31am-2:33am and 2:46am-2:48am.