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Performance Management and Capacity Planning Solution GigaWorld 2004

Performance Management and Capacity Planning Solution GigaWorld 2004. TeamQuest Solution. Complete software suite for Performance Management & Capacity Planning Cross-platform support for all major vendors (Sun Solaris, IBM AIX, HP-UX, etc) Integrates with SNMP console applications

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Performance Management and Capacity Planning Solution GigaWorld 2004

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  1. Performance Management andCapacity Planning SolutionGigaWorld 2004

  2. TeamQuest Solution • Complete software suite for Performance Management & Capacity Planning • Cross-platform support for all major vendors (Sun Solaris, IBM AIX, HP-UX, etc) • Integrates with SNMP console applications • Flexible software that is easy to customize and adapt to heterogeneous IT environments • Extremely low resource consumption • Little manual labor required for daily operation

  3. Architecture

  4. Data Collection Application Agents #!/bin/bash User Agents OS/Kernel Agents

  5. Data Collection Aggregation Real time sampling 10 Minute Data Points 1 Hour Data Points 8 Hour Data Points Event Logs & Process Table 1 Minute Data Points TabularData NumericalData 1 Day 8 Hours 8 Days 5 Weeks 13 Months

  6. Complete Process Information 08:01 08:02 08:03 08:04 08:05 TQ TQ TQ TQ TQ /var/adm/pacct

  7. Workload Activity

  8. Trend Alarm Linear Trend Analysis (LTA) 1 Hour Projection Data Points 5 Weeks CPU runq_sz, 21 day projection

  9. Exception Alarm Short Term Analysis (STA) 1 Hour Data Points Day-of-Week Data Points Percent CPU by workload, typical week Mon-Fri 5 Weeks 7 Days

  10. Enterprise Solution Analysis SummaryReports CapacityPlanning

  11. Management Reports

  12. Customer Reports Internal External

  13. Alarms Thresholds and severities “All-clear” notification Qualifiers

  14. Alarm Notification Options TQ Alarm Table SNMP trap to console Run command

  15. Integration with SNMP console

  16. Central Administration TeamQuest Administration Server Workloads Reductions Alarms Solaris Reductions AIX HP-UX Systems HP-UX Workloads Workloads Alarms Sun Reductions AIX HP-UX AIX Systems Alarms Workloads Sun Alarms AIX Reductions HP-UX Solaris Systems

  17. Deployment • Central deployment with replicated installation ”Prototype” system Network drive with: TQ install binaries “Response” file Key file “Response” file ./install.sh ./install.sh ./install.sh ./install.sh ./install.sh

  18. Capacity Planning • Overview • Basics of Modeling • Example: Server Consolidation

  19. Overview Performance Analysis Capacity Planning • Daily Follow-up • Baselining • Troubleshooting • Tracing • Bottlenecks • Correlation Analysis • Historical & Real-time Analysis • Optimization of OS/apps • Stress Testing Trending Modeling • Statistical Trends • Regression-based • Mathematical Simulation • Model-based • Growth Predictions • Server Consolidation TQView TQModel TQView TQWeb TQAlert

  20. Stretch Factor • In the simplest terms, modeling is about finding the point where the server starts to slow down. • This state occurs when the StretchFactor reaches 2 in TeamQuest Model • Stretch Factor is a general indication of the performance of the server. • At Stretch Factor 2 the performance of the server starts to degrade exponentially.

  21. Example • Six stand-alone servers will be consolidated into one • All existing applications will be moved to the sixth • The sixth server should also be able to handle some growth

  22. Server Utilization • TeamQuest View and Workloads allow us to analyze each server in order to get a complete picture of the resource utilization on the servers involved in the consolidation exercise. • The resource utilization is measured as a TeamQuest Workload, which is a logical grouping of the work being done on the server.

  23. Peak Hour • Select a time for each server. • Our goal is to size the sixth server for the worst case, i.e. all application may peak at the same time.

  24. Get input file • Extract the chosen time frame, download the data file and open it in TeamQuest Model Web Browser TeamQuest Model

  25. Calibrate • Calibrate the downloaded data file in TeamQuest Model. • A calibrated model can be manipulated and allows us ask what-if questions, simulate different growth scenarios and test different hardware. Raw data Calibration Calibrated Model

  26. Merge models • Merge the calibrated models into the target system model. By merging the models we are in effect moving all applications and load to one server. Merge

  27. Stretch factor • Solve the merged model and verify the results. Generally speaking, a stretch factor of less than 2 signifies a successful consolidation. The sixth server will be able to handle the extra load from other five with existing hardware. Before the consolidation After the consolidation

  28. Increase load • Question: How will our consolidated server respond to a 5% increase per month of the “Order” workload?

  29. Predicted stretch factor • Answer: the server will hit its limit in June when the stretch factor reaches 2. • It is important to follow-up on predictions made so that future predictions are more realistic and accurate.

  30. Summary • Optimize utilization levels on existing servers • Predict performance problems with trend alarms and exception reports • Test new applications, consolidate servers, and upgrade hardware with confidence • Create workloads and know exactly how much resources are consumed by different customers • Consolidate performance data into enterprise databases for cross-server reporting • Spend less time monitoring your servers and more time on productive work

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