IBM Performance Optimizaiton Toolkit for Rational Performance Tester
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Presented at IBM Rational Software Development Conference in 2006
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IBM Performance Optimizaiton Toolkit for Rational Performance Tester
- 1. IBM Rational Software Development Conference 2006 Session: SQ11© 2006 IBM Corporation ® IBM Performance Optimization Toolkit (IPOT) for IBM Rational Performance Tester (RPT) Ashish Patel (Software Developer) ashishp@ca.ibm.com Eric Labadie (Senior Advisory Analyst) labadie@ca.ibm.com IBM Canada
- 2. IBM Rational Software Development Conference 2006 Session: SQ11 Agenda IBM Performance Optimization Toolkit (IPOT) overview IT Lifecycle Management Problem Determination by Example Simple Performance Test Resource Monitoring during Performance Testing Root Cause Analysis using Application Trace data Demo (30 min) Online References Q&As (10 min)
- 3. IBM Rational Software Development Conference 2006 Session: SQ11 IBM Performance Optimization Toolkit Overview Who are the IPOT users? Any developer who wants to identify root cause of performance problems and accelerate problem determination occurring in development environment. Any tester / performance tester who wants to identify root cause of performance problems and accelerate problem determination occurring in test environment. Any support developer who wants to identify root cause of performance problems and accelerate problem determination occurring in production environment.
- 4. IBM Rational Software Development Conference 2006 Session: SQ11 IBM Performance Optimization Toolkit Overview Why would they use IPOT? IPOT provides transaction decomposition for application optimization Allows the developer/tester to monitor a distributed application in real-time Provides a Data Collection Infrastructure (DCI) for real-time monitoring Integrates with Rational Software Development Platform IPOT accelerates problem determination by correlating the different data collection views (logging, performance and resource monitoring data) by time. IPOT allows to import data from production environment and visualize it for analysis and correlation in the development/test environments.
- 5. IBM Rational Software Development Conference 2006 Session: SQ11 IT Lifecycle Management ITBusiness Application Development Problem Determination Development Team Deployment2 1 3 Operations Team
- 6. IBM Rational Software Development Conference 2006 Session: SQ11 Problem Determination by Example An example: Plants By WebSphere Application ServerWeb Server Database Server Application Server Data Collection Infrastructure IPOT Agent ITM Agent ITM Agent Steps to collect resource data Steps to collect application performance data ITM Agent
- 7. IBM Rational Software Development Conference 2006 Session: SQ11
- 8. IBM Rational Software Development Conference 2006 Session: SQ11 Run
- 9. IBM Rational Software Development Conference 2006 Session: SQ11
- 10. IBM Rational Software Development Conference 2006 Session: SQ11 Overlay resource counters with the test results Resource counters are statistical data that change over time Data is collected from statistical resource data collecting agents, such as ITM agents, Windows Performance Monitor, Rstatd Correlate the resource data with the results to identify the location where performance degradation might have occurred Problem determination in real-time Steps to Problem Determination
- 11. IBM Rational Software Development Conference 2006 Session: SQ11
- 12. IBM Rational Software Development Conference 2006 Session: SQ11
- 13. IBM Rational Software Development Conference 2006 Session: SQ11
- 14. IBM Rational Software Development Conference 2006 Session: SQ11 Run
- 15. IBM Rational Software Development Conference 2006 Session: SQ11
- 16. IBM Rational Software Development Conference 2006 Session: SQ11
- 17. IBM Rational Software Development Conference 2006 Session: SQ11
- 18. IBM Rational Software Development Conference 2006 Session: SQ11 Architecture: Statistical Data Target System IBM Tivoli Monitoring Data Warehouse Management Server SOAPServer Presentation System IPOT Web Service Client RPT Eclipse Platform ITM Agent (Linux OS) ITM Agent (Windows OS) ITM Agent (Unix OS) ITM Agent (DB2) … Internet (HTTP/HTTPs)
- 19. IBM Rational Software Development Conference 2006 Session: SQ11 Root cause analysis using application trace data Performance metrics measured during tracing helps to drill down to possible causes of performance degradation Real-time data collection using the Data Collection Infrastructure (DCI) for ARM-instrumented applications Application Response Measurement (ARM) is an open standard. Steps to Problem Determination
- 20. IBM Rational Software Development Conference 2006 Session: SQ11
- 21. IBM Rational Software Development Conference 2006 Session: SQ11
- 22. IBM Rational Software Development Conference 2006 Session: SQ11
- 23. IBM Rational Software Development Conference 2006 Session: SQ11
- 24. IBM Rational Software Development Conference 2006 Session: SQ11
- 25. IBM Rational Software Development Conference 2006 Session: SQ11
- 26. IBM Rational Software Development Conference 2006 Session: SQ11
- 27. IBM Rational Software Development Conference 2006 Session: SQ11 Architecture: Performance Data Target SystemPresentation System IPOT RPT Eclipse Platform Performance Schedule Performance Test AgentController AgentController HTTP Request (HTTP Header includes ARM_CORRELATOR) Data Collection Infrastructure Application Server Application IPOT Agent
- 28. IBM Rational Software Development Conference 2006 Session: SQ11 Analyze applications deployed to a pre-production or production environment using Tivoli products Provides a developer a realistic view of the events in a production environment for root cause analysis Import performance data from IBM Tivoli Composite Application Manager (ITCAM) products after the application has executed Import statistical data from IBM Tivoli Monitoring (ITM) after the application has executed Steps to Problem Determination
- 29. IBM Rational Software Development Conference 2006 Session: SQ11 Import Performance Data
- 30. IBM Rational Software Development Conference 2006 Session: SQ11 Import Performance Data
- 31. IBM Rational Software Development Conference 2006 Session: SQ11 Import Performance Data
- 32. IBM Rational Software Development Conference 2006 Session: SQ11 Import Performance Data
- 33. IBM Rational Software Development Conference 2006 Session: SQ11 Import Performance Data
- 34. IBM Rational Software Development Conference 2006 Session: SQ11 Import Performance Data
- 35. IBM Rational Software Development Conference 2006 Session: SQ11
- 36. IBM Rational Software Development Conference 2006 Session: SQ11 Architecture: Import Performance Data Target System IBM Tivoli Composite Application Manager Data Warehouse Management Server WebServices Presentation System IPOT Web Service Client RPT Eclipse Platform Management Agent Management Agent Management Agent Management Agent … Internet (HTTP/HTTPs)
- 37. IBM Rational Software Development Conference 2006 Session: SQ11 Import Statistical Data
- 38. IBM Rational Software Development Conference 2006 Session: SQ11 Import Statistical Data
- 39. IBM Rational Software Development Conference 2006 Session: SQ11 Import Statistical Data
- 40. IBM Rational Software Development Conference 2006 Session: SQ11 Import Statistical Data
- 41. IBM Rational Software Development Conference 2006 Session: SQ11 Import Statistical Data
- 42. IBM Rational Software Development Conference 2006 Session: SQ11
- 43. IBM Rational Software Development Conference 2006 Session: SQ11 Integration IBM Rational Products RPT: Rational Performance Tester DCI: Data Collection Infrastructure J2EE Application Servers IBM WebSphere Application Server™ (WAS) BEA WebLogic™ IBM Tivoli Products TMTP: Tivoli Monitoring for Transaction Performance ITCAM for RTT: IBM Tivoli Composite Application Manager for Response Time Tracking ITCAM for WebSphere: IBM Tivoli Composite Application Manager for WebSphere ITM: IBM Tivoli Monitoring
- 44. IBM Rational Software Development Conference 2006 Session: SQ11 Demo
- 45. IBM Rational Software Development Conference 2006 Session: SQ11 Online Reference Download Forum
- 46. IBM Rational Software Development Conference 2006 Session: SQ11 Questions
- 47. IBM Rational Software Development Conference 2006 Session: SQ11 Eric Labadie Ashish Patel http://www-128.ibm.com/developerworks/rational/library/05/523_perf/ Thank You
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- i/t has to be ondemand just as much as the business has to be ondemand w/ their clients => IBM has to respond to that - Optimize application before deploying to prevent problems before it happens in the first place Reduce business downtimewhile accelerating business value throughput… Quickly discover and understand application-level errors even after deployment Speed Tivoli-aware application fix and (re)build Optimize and accelerate (re)deployment …by bridging developmentand operations teams
- Example: Trying to run a test to identify if performance problems exist in a multi-user environment. Diagram: Can be distributed on separate machines. Workbench collect performance and resource monitoring data import data from historical systems Data Collection Infrastructure (DCI) Data Collection Agent IBM Tivoli Data Collection IBM Remote Agent Controller IPOT Agent is reported the ARM Events. ARM Events are collected and organized into a transactional hierarchy, from the root transaction to all of its sub-transactions. This hierarchy is then converted into TPTP Trace events and sent to the Presentation System. Need DCI installed on the Presentation System if trying to Profile J2EE Performance Metrics while executing a Performance Schedule or Test. Resource Monitoring We provide data collection (via the RAC) from Windows/Linux machine, JBoss/JOnas IPOT adds value by having the ITM infrastructure in place because they support a wide array of ITM agents
- Here is what you can do today with RPT….
- Today there is a need to look into a specific page and how it’s page elements compare. Viewing performance and statistical data for a particular page helps to isolate the exact location of the problem.
- Steps to determine the cause of the problem: Overlay resource counters with the test results. - Resource counters are statistical data that change over time - Data is collected from statistical resource data collecting agents, such as ITM agents Correlate the resource data with the results to identify the location where performance degradation might have occurred. - Analysis method can be used by overlaying the resource counters selected for real-time data collection during the execution of the test/schedule
- Now, let’s try to monitor resource counters across multiple systems to understand the SUT behavior.
- We can import and monitor resource monitoring data from multiple sources…
- In this example, we will be monitoring counters which are monitored by ITM (IBM Tivoli Monitoring).
- By clicking the Run button we start monitoring the selected counters…
- As the test got executed, we now see the RPT performance report and the resource monitoring counters.
- Part of the RPT reports we have Response vs Time reports
- The user can drag and drop counters on top of the existing reports to customize them. Other useful counters to analyze, other than processor time, are memory usage, disk activity, network activity. The combination of these counters will help to better understand if there is a lack of resources or if there actually is an application-related problem.
- This is the oversall architecture for pulling resource monitoring data from ITM
- Steps to determine the cause of the problem: using performance data Collect performance data using the DCI Performance data allows the tester and developer to peer into the behaviour of the application or service at a programmatic level (ie. The method level) This approach provides solid evidence of where the potential problem is located and increases efficiency in problem determination between the tester and developer, thereby, effectively reducing the time to identify and diagnose performance problems. Real-time data collection using the Data Collection Infrastructure (DCI) for ARM-instrumented applications Application Response Measurement (ARM) is an open standard from OpenGroup
- Now that we know we have a performance problem with the test case, let’s enable ARM monitoring for the transaction decomposition performance…
- …and enable it as well in the performance schedule.
- And now launch the test schedule in transaction monitoring mode.
- Now, the user gets the UML sequence diagram which shows the transaction decomposition associated with the test cases inside the test schedule. End to end transaction UML view with a performance problem for the problematic transaction. On the scale on the right, the user can see the different shades of red beside each method calls. The darker red on the scale, the more time is spent in this location in the problematic transaction. The user can then jump to the source code from this view.
- The user can the switch to the Method details views to view as well the time spent in the descendant methods called from this transaction. The user can then jump to the source code from this view.
- As well, we provide method statistics views showing to the user how many times a methods was called and what is the average time spent in this method. The user can then jump to the source code from this view.
- Finally, the user can go to source code from the previous views to identify performance problem
- Workbench collect performance and resource monitoring data import data from historical systems Data Collection Infrastructure (DCI) Data Collection Agent IBM Tivoli Data Collection IBM Remote Agent Controller Workflow: The RPT client is the edge of the transaction (where ARM transactions are first generated). Therefore, all page are transacted from the presentation system, which behaves similar to a browser, by placing HTTP requests for all page elements (belonging to their respective pages). For all HTTP Requests, RPT adds the ARM_CORRELATOR header attribute to the request. Multiple RPT clients can generate the same load for the same transactions and they will be collected by the ARM engine independently. Anything downstream from the RPT client (for example a webserver or J2EE appserver) must be instrumented with J2EE Monitoring Component (or Tivoli Data Collection, which consists of probes or hooks) that knows how to detect the ARM_CORRELATOR header attribute and then make the appropriate ARM calls to the ARM engine. Once the probe makes the ARM call, the transactions are all treated the same by the ARM engine. In order to see “into” the application (at the method level) when the RPT test/schedule is executed, the Execution Environments involved muse be instrumented, just the same as one would do with TMTP or the IPOT DCI, so that the RPT HTTP Requests can be correlated with the AppServer’s behavious. Caspian: Architecture will change so that IPOT is not dependent on RPT, however, RPT becomes dependent on IPOT. Allowing other products to leverage the toolkit. IPOT Agent is reported the ARM Events. ARM Events are collected and organized into a transactional hierarchy, from the root transaction to all of its sub-transactions. This hierarchy is then converted into TPTP Trace events and sent to the Presentation System. Need DCI installed on the Presentation System if trying to Profile J2EE Performance Metrics while executing a Performance Schedule or Test.
- Steps to determine the cause of the problem: using performance data Collect performance data using the DCI Performance data allows the tester and developer to peer into the behaviour of the application or service at a programmatic level (ie. The method level) This approach provides solid evidence of where the potential problem is located and increases efficiency in problem determination between the tester and developer, thereby, effectively reducing the time to identify and diagnose performance problems. Real-time data collection using the Data Collection Infrastructure (DCI) for ARM-instrumented applications Application Response Measurement (ARM) is an open standard from OpenGroup
- In a large scale environment, we use TMTP, TCAMfWebsphere and TCAMfRTT to monitor the transactions. Now, let’s import data from these Tivoli products and analyze it in the RPT workbench.
- The user needs to specify the user id and password to pull the data from the Tivoli Management Server.
- And then specify when the failure occurred on the system.
- Then the user picks up the TCAM/TMTP policy which triggered the error.
- Then, the user select the server where the transaction was initiated from.
- Then the user picks up the transaction instance that violated the policy.
- The user can now investigate the transaction performance problem inside the RPT tooling. End to end transaction UML view with a performance problem for the problematic transaction. On the scale on the right, the user can see the different shades of red beside each method calls. The darker red on the scale, the more time is spent in this location in the problematic transaction. The user can then jump to the source code from this view.
- This is the architecture overview for pulling the data from the TCAM products.
- The user may also import historical resource monitoring data from ITM.
- The user specifies the userid and password to access ITM server.
- The user then specifies the time range for the data to import.
- The user then picks up the machines…
- and resource counters to import data for.
- Then the user can look at the imported data inside the RPT workbench.
- Here is the list of IBM products that IPOT can pull data from…