Introduction to enterprise applications capacity planning

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The presentation provides an introduction to enterprise applications capacity planning using queuing models. Oracle’s Consulting uses presented methodology to estimate hardware architecture and …

The presentation provides an introduction to enterprise applications capacity planning using queuing models. Oracle’s Consulting uses presented methodology to estimate hardware architecture and capacity of planned for deployment enterprise applications for Oracle customers.

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  • 1. <Insert Picture Here>Introduction to enterprise applications capacity planningusing queuing modelsLeonid Grinshpan, Ph.D.Consulting Technical Director
  • 2. Disclaimer The following presentation is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality All brands and trademarks mentioned are the property of their owners. 2
  • 3. Presentation’s goal The presentation provides an introduction to enterprise applications capacity planning using queuing models Oracle’s Consulting uses presented methodology to estimate hardware architecture and capacity of planned for deployment enterprise applications for Oracle customers 3
  • 4. Presentation’s structureSection 1Do we really need modeling for capacity planning?Section 2Methodology of enterprise applications capacity planningSection 3Solving models and evaluating what-if scenarios 4
  • 5. Section 1DO WE REALLY NEED MODELING FORCAPACITY PLANNING?Can we just go by our gut feeling? 5
  • 6. Quiz 1. Ticket reservation application• A ticket reservation application is deployed on one server with 8 CPUs.• System delivers 10 seconds response time and utilizes server’s CPU at 50% under workload described in a table: Transaction name Number of users Transaction rate Ticket Reservation (TR) 250 6 per user per hourQ. How many more users an application can support without response time degradation exceeding 10% ? 6
  • 7. Quiz 1. Ticket reservation application (cont) 7
  • 8. Quiz 2. Ticket reservation and on-line payment applications• A ticket reservation application per Quiz 1 uses only 50% of 8 CPU server capacity. Let’s deploy on the same server on-line payment application.• Workload for both applications is described in a table: Transaction name Number of users Transaction rate Ticket Reservation (TR) 250 6 per user per hour On-line payment (OLP) ???? 10 per user per hourQ. How many on-line payment users system can support delivering on-line payment transaction time 8 seconds? 8
  • 9. Quiz 2. Ticket reservation and on-line payment applications (cont) 9
  • 10. Section 2METHODOLOGY OF ENTERPRISEAPPLICATIONS CAPACITY PLANNING 10
  • 11. Generalized enterprise application architecture 11
  • 12. What is a main application performance indicator from the users perspective? 12
  • 13. Mapping application into queuing model Hardware server representation Total time in node = time in waiting queue + time in processing unit 13
  • 14. Mapping application into queuing model (cont 2) 14
  • 15. Mapping application into queuing model (cont 3)The relationships between the components of a real system and the components of its model Component of application Matching object in queuing model Users Node “Users” Web server Node “Web server” Application and Database Node “A&D server” server Requests from users Cars 15
  • 16. Transaction response time and transaction profile Transaction time is a time spent in “cloud” 16
  • 17. Transaction response time and transaction profile (cont 2) 17
  • 18. Input data for capacity planning1. Workload characterization List of business transactions Number of users per each business transaction Per each transaction a number of transactions per user per hour (transaction rate). Transaction name Number of users Transaction rate Report ABC 20 12 Business Rule X 10 8 Consolidation Y 5 3 18
  • 19. Input data for capacity planning (cont 2) 2. Transactions profilesTransaction profile is comprised of the time intervals a transaction has spent insystem servers it has visited when application was serving only that singletransaction Transaction name Service demand (seconds) Web server A&D server Report ABC 0.5 0.5 Business Rule X 0.5 2.5 Consolidation Y 0.5 9.5 19
  • 20. Building and solving models using open source Java Modeling ToolOpen source software package Java Modeling Tools (JMT) can be downloaded from http://jmt.sourceforge.net/. 20
  • 21. Definition of nodes in JMT Node “Users” has as many processing units as total number of users Node “Web server” has one processing unit Node “A&D server” has one processing unit 21
  • 22. Definition of workload and transaction profile inJMT 22
  • 23. Solving JMT modelReport ABC time is 0.52 + 0.57 = 1.09 sec Business Rule X time is 0.52 + 2.84 = 3.36 sec Consolidation Y time is 0.52 + 10.78 = 11.30 sec 23
  • 24. Solving JMT model (cont 2)Total utilization of Web server is 4.6% and A&D server is 12.7% Transaction Business Rule X utilizes Web server at 1.1% and A&D server at 5.5% Transaction Consolidation Y utilizes Web server at 0.2% and A&D server at 3.9% 24
  • 25. What is needed for enterprise application capacity planning ?1. Description of system architecture (hardware servers , hosted software components)2. Input data:  Workload characterization (flow of business transactions from system users)  Transaction profiles (service demand from single transaction)3. Model solver 25
  • 26. Section 3SOLVING MODELS AND EVALUATINGWHAT-IF SCENARIOS 26
  • 27. Open source vs. commercial model solversOpen source solvers Limited functionality Lack of extensive and up-to-day libraries of hardware platformsCommercial solvers Accept input data in a form of hardware and software specifications and benchmarks Automate study of multiple what-if scenarios Components of broader suites Include collectors of input data that can be feed into model directly 27
  • 28. Building and solving models using commercial products Three-tier system Transaction profiles Transaction Service demand (seconds) name Web server App server DB server Report ABC 0.5 0.2 0.3Business Rule X 0.5 1.0 1.5Consolidation Y 0.5 7.0 2.5 28
  • 29. Building and solving models using commercialproducts (cont 2) Specification of hardware servers Description of business transactions 29
  • 30. Building and solving models using commercialproducts (cont 3) Transaction profiles 30
  • 31. Building and solving models using commercialproducts (cont 4) Description of users 31
  • 32. Building and solving models using commercial products (cont 5) MAIN MODEL DELIVERABLES Average transaction response time for each transaction Utilization of each hardware server Transaction time (seconds) Utilization of system servers (%) 32
  • 33. Common what-if scenarios1. Changing hardware platform2. Analysis of different operating systems3. Workload variations4. Assessment of impact of network and remote users5. Changing number of cores and CPUs6. Server farms7. Redistribution of application’s software components 33
  • 34. Analysis of what-if scenarios Faster Application server All three servers are faster 34
  • 35. Analysis of what-if scenarios (cont 2) Transaction time (seconds) Transaction time (seconds) Baseline system System with fast Application server 35
  • 36. Analysis of what-if scenarios (cont 3) Transaction time (seconds) Transaction time (seconds)System with fast Application server System with three fast servers 36
  • 37. Analysis of what-if scenarios (cont 3) Utilization of system servers (%) 37
  • 38. Example of an Oracle enterprise applicationproduction deployment DO WE REALLY NEED MODELING FOR CAPACITY PLANNING? Can we just go by our gut feeling? 38
  • 39. To learn more about enterprise applications capacity planning please check author’s book“Solving Enterprise Applications Performance Puzzles: Queuing Models to the Rescue” (available in bookstores and from Web booksellers) http://www.amazon.com/Solving-Enterprise- Applications-Performance- Puzzles/dp/1118061578/ref=sr_1_1?ie=UTF8& qid=1326134402&sr=8-1https://www.amazon.com/author/leonid.grinshpan Contact Leonid Grinshpan at: leonid.grinshpan@oracle.com 39