Multiple Dimensions of Load Testing
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Load testing is an important part of the performance engineering process. It remains the main way to ensure appropriate performance and reliability in production. It is important to see a bigger picture beyond stereotypical, last-moment load testing. There are multiple dimensions of load testing: environment, load generation, testing approach, life-cycle integration, feedback and analysis. This paper discusses these dimensions and how load testing tools support them.
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![Agenda
• Load Testing
• Five [New] Load Testing Dimensions
-Environment
-Load Generation
-Testing Approach
-Life-Cycle Integration
-Feedback and Analysis
2
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Multiple Dimensions of Load Testing
- 1. Multiple Dimensions of Load Testing Alexander Podelko alex.podelko@oracle.com alexanderpodelko.com/blog @apodelko Performance & Capacity 2015 by CMG November 2, 2015
- 2. Agenda • Load Testing • Five [New] Load Testing Dimensions -Environment -Load Generation -Testing Approach -Life-Cycle Integration -Feedback and Analysis 2 Disclaimer: The views expressed here are my personal views only and do not necessarily represent those of my current or previous employers. All brands and trademarks mentioned are the property of their owners.
- 3. Load Testing Applying multi-user synthetic load to the system – Load testing – Performance testing – Stress testing – Scalability testing – Volume testing – Reliability testing – Concurrency testing – Realistic Testing – Endurance testing – Longevity testing – Soak testing – Stability testing 3
- 4. Load Testing Process Collect Requirements Define Load Run Tests Analyze Results Done Modify System Goals are met Goals are not met 4 Traditional View
- 5. The Stereotype • Load / Performance Testing is: – Last moment before deployment – Last step in the waterfall process – Protocol level record-and-playback – Large corporations – Expensive tools requiring special skills – Lab environment – Scale-down environment – … 5
- 6. Load Testing • Traditional load testing is not enough anymore • New industry trends change a lot – Cloud – Continuous Integration / Delivery / Deployment – DevOps – Agile • Some even say that load testing is not needed anymore – Due to other ways to mitigate performance risk 6
- 7. Performance Risk Mitigation • Single-user performance engineering – Profiling, WPO, single-user performance • Software Performance Engineering – Modeling, Performance Patterns • Instrumentation / APM / Monitoring – Production system insights • Capacity Planning/Management – Resources Allocation • Continuous Integration / Deployment – Ability to deploy and remove changes quickly 7
- 8. But all of them don’t replace load testing: Load testing complements them in several important ways ! 8
- 9. Can System Handle Peak Load? • You can’t know without testing: 9
- 10. Verify Multi-User Performance • Single-user improvement may lead to multi- user performance degradation 10
- 11. What Else Load Testing Adds • Performance optimization – Apply exactly the same load – See if the change makes a difference • Debugging/verification of multi-user issues • Testing self-regulation functionality – Such as auto-scaling or changing the level of service depending on load 11
- 12. So What Is Going On? • I believe that load testing is here to stay, but should fully embrace the change – Not one-time, to become dynamic • Many things that were practically given became a hard choice of a continuum of options (dimension vs. point) – Environment, Load Generation, Testing Approach, Life-Cycle Integration, Feedback and Analysis 12
- 13. Agenda • Load Testing • Five [New] Load Testing Dimensions -Environment -Load Generation -Testing Approach -Life-Cycle Integration -Feedback and Analysis 13
- 14. Load Testing Process Collect Requirements Define Load Run Tests Analyze Results Done Modify System Goals are met Goals are not met 14 Environment ?
- 15. Deployment • Lab vs. Service (SaaS) vs. Cloud (IaaS) – For both the system and load generators • Test vs. Production • No best solution, depends on your goals / system 15
- 16. Scenarios • System validation for high load – Outside load (service or cloud), production system – Wider scope, lower repeatability • Performance optimization / troubleshooting – Isolated lab environment – Limited scope, high repeatability • Testing in Cloud – Lowering costs (in case of periodic tests) – Limited scope, low repeatability 16
- 17. Find Your Way • If performance risk is high it may be a combination of environments, e.g. – Outside tests against the production environment to test for max load – Lab for performance optimization / troubleshooting – Limited performance environments to be used as part of continuous integration 17
- 18. Scaling • Becomes critical as you get to a large number of virtual users • The number of supported users per unit of computing power may differ drastically – Depending on tool, protocol, scenario, system… • If you need deploy it on a large number of machines automation would be helpful 18
- 19. Agenda • Load Testing • Five [New] Load Testing Dimensions -Environment -Load Generation -Testing Approach -Life-Cycle Integration -Feedback and Analysis 19
- 20. Load Testing Process Collect Requirements Define Load Run Tests Analyze Results Done Modify System Goals are met Goals are not met 20 Create Test Assets
- 21. Record and Playback: Protocol Level Load Testing Tool Virtual Users ServerLoad Generator Application Network 21
- 22. Considerations • Usually doesn't work for testing components • Each tool support a limited number of technologies (protocols) • Some technologies are very time-consuming • Workload validity in case of sophisticated logic on the client side is not guaranteed 22
- 23. Record and Playback: UI Level 23 Load Testing Tool Virtual Users ServerLoad Generator Application NetworkBrowsers
- 24. Considerations • Scalability – Still require more resources • Supported technologies • Timing accuracy • Playback accuracy – For example, for HtmlUnit 24
- 25. Programming Load Testing Tool App. Virtual Users ServerLoad Generator Application Network API 25
- 26. Considerations • Requires programming / access to APIs • Tool support – Extensibility – Language support • May require more resources • Environment may need to be set 26
- 27. Agenda • Load Testing • Five [New] Load Testing Dimensions -Environment -Load Generation -Testing Approach -Life-Cycle Integration -Feedback and Analysis 27
- 28. Load Testing Process Collect Requirements Define Load Run Tests Analyze Results Done Modify System Goals are met Goals are not met 28 Sounds as running a fixed set of tests, doesn’t it?
- 29. Mentality Change • Making performance everyone’s job • Late record/playback performance testing -> Early Performance Engineering • System-level requirements -> Component-level requirements • Record/playback approach -> Programming to generate load/create stubs • "Black Box" -> "Grey Box”
- 30. Performance Testing • Usually is not separated from: – Tuning • System should be properly tuned – Troubleshooting / Diagnostics • Problems should be diagnosed further to the point when it is clear how to handle them – Capacity Planning / Sizing • "Pure" performance testing is rare – Regression testing ?
- 31. Exploratory Testing • Rather alien for performance testing, but probably more relevant than for functional testing • We learn about system’s performance as we start to run test – Only guesses for new systems • Rather a performance engineering process bringing the system to the proper state than just testing 31
- 32. Test Approach Dimension NewWell-known System Testing Approach Exploratory / Agile Automated / Regression Traditional
- 33. Test Management • Managing test execution / collecting results • Virtual users coordination, e.g.: – Synchronization points – Data exchange – Sophisticated scheduling • Environment simulation, e.g.: – Browser Simulation – Network simulation (including mobile) – IP spoofing 33
- 34. Agenda • Load Testing • Five [New] Load Testing Dimensions -Environment -Load Generation -Testing Approach -Life-Cycle Integration -Feedback and Analysis 34
- 35. Load Testing Process Collect Requirements Define Load Run Tests Analyze Results Done Modify System Goals are met Goals are not met 35 No integration points at all !
- 36. Agile Support • Agile / CI support becoming the main theme • Integration with Continuous Integration Servers – Jenkins, Hudson, etc. – Several tools announced integration recently – Making a part of automatic build process • Automation support • Easiness to use • Support of newest technologies 36
- 37. Automation: Difficulties • Complicated setups • Long list of possible issues • Complex results (no pass/fail) • Not easy to compare two result sets • Changing Interfaces • Tests may be long
- 38. Automation: Considerations • You need know system well enough to make meaningful automation • If system is new, overheads are too high – So almost no automation in traditional environments • If the same system is tested again and again – It makes sense to invest in setting up automation • Automated interfaces should be stable enough – APIs are usually more stable on early stages
- 39. Tool Support • Not much tool support was until recently • Some vendors claimed that their load testing tool better fits agile processes – Often it meant that the tool is a little easier to use • Was difficult to find what is available – Ability to automate: command line, API, data access – Ability to extend scripts – Supported technologies
- 40. Tool Support: Recent Developments • Recently agile support became the main theme – A lot of new developments • Integration with Continuous Integration Servers – Several tools announced integration recently • Cloud integration • Support of newest technologies
- 41. Agenda • Load Testing • Five [New] Load Testing Dimensions -Environment -Load Generation -Testing Approach -Life-Cycle Integration -Feedback and Analysis 41
- 42. Load Testing Process Collect Requirements Define Load Run Tests Analyze Results Done Modify System Goals are met Goals are not met 42 Isn’t so simple anymore
- 43. Reporting and Analysis • Good integrated reporting and analysis greatly increases efficiency – Getting all data in one place and synchronized – Integration of monitoring data is a great help • Weak spot of many open source tools 43
- 44. Monitoring • System level • Application level (APM) – AppDynamics, New Relic, Dynatrace, etc. – Many tools have integration • Integration allows analyze monitoring data together with test results 44
- 45. The Main Change in Monitoring • Configuration becomes dynamic, changing on the fly • Auto scaling, auto provisioning, etc. – Challenge to monitor all moving parts – Challenge to compare results of dynamic configurations – Shift to application monitoring 45
- 46. The Main Change in Analysis • Not only comparison with the requirements • Many different forms of analysis depending on the tests – Adjusting to configuration / type of the test • Component testing – Automatic analysis / alerting • Continuous Integration / Delivery / Deployment – Input for tuning / optimization / sizing 46
- 47. Summary • The industry is rapidly changing – performance testing should change too – Fully embrace agile • Five [new] dimensions introduced by the changes – Environment, Load Generation, Testing Approach, Life-Cycle Integration, Feedback and Analysis • Good tools help, but there is no best tool – it depends on your needs 47