Continuous Performance Testing: The New Standard
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Continuous Performance Testing: The New Standard

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In the past several years the software development lifecycle has changed significantly with high-speed software releases, shared application services, and platform virtualization. The traditional ...

In the past several years the software development lifecycle has changed significantly with high-speed software releases, shared application services, and platform virtualization. The traditional performance assurance approach of pre-release testing does not address these innovations. To maintain confidence in acceptable performance in production, pre-release testing must be augmented with in-production performance monitoring. Obbie Pet describes three types of monitors—performance, resource, and VM platform—and three critical metrics fundamental to isolating performance problems—response time, transaction rate, and error rate. Obbie reviews techniques to acquire and interpret these metrics, and describes how to develop a continuous performance monitoring process. In conjunction with pre-release testing, this monitoring can be woven into a single integrated process, offering a best bet in assuring performance in today’s development world. Take away this integrated process for consideration in your own shop.

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Continuous Performance Testing: The New Standard Document Transcript

  • 1.        Session    Presented by:  Obbie Pet  T       Brought to you by:      340 Corporate Way, Suite   Orange Park, FL 32073  888‐2 W10  Concurrent 4/9/2014    2:00 PM          “Continuous Performance Testing:   The New Standard”      icketmaster             300, 68‐8770 ∙ 904‐278‐0524 ∙ sqeinfo@sqe.com ∙ www.sqe.com 
  • 2. Obbie Pet Ticketmaster   Obbie Pet has twenty years of experience in QA, as tester, test lead, and QA manager. For the past thirteen years, Obbie has focused on performance testing in the area of Internet ticketing (Tickets.com, LiveNation, Ticketmaster) and in the insurance field (Wellpoint). He is certified on the LoadRunner testing tool by both Mercury and HP. Five years ago, Obbie realized that achieving performance assurance in production required expanding beyond just testing to include performance monitoring. His focus now is sharing these ideas and implementing monitoring solutions in support of performance assurance. Read more about Obbie and his thoughts on performance assurance at QAStrategy.com.
  • 3. Continuous Performance Testing: The New Standard A Performance Paradigm Shift 4/9/2014 ObbiePet@ticketmaster.com
  • 4. Obbie Pet Sr Performance Engineer Ticketmaster.com Internet ticketing space 10+ years Ticketmaster Blog: http://tech.ticketmaster.com/ Contact: ObbiePet@ticketmaster.com or opet@qastrategy.com
  • 5. Ticketmaster • 450M Tickets processed (annual) • 180K Events (annual) • 12K clients • 19 countries • >8M mobile tickets in 2012
  • 6. Agenda The problem – Old paradigm SDLC – New paradigm SDLC – Old paradigm’s test tool isn’t cutting it. The solution – Need a second tool - Monitoring – Monitoring use case – Monitoring dashboard examples Takeways – Performance Assurance process for your shop
  • 7. Old SDLC Paradigm • Quarterly releases, low velocity change • Monolithic websites and applications • Dedicated hardware
  • 8. Old SDLC performance assurance • Pre-Release testing • Production candidate staged • High demand is simulated • Problems are detected and fixed • Executed before every release • Works great for old SDLC • Newtons 3rd law
  • 9. New SDLC Paradigm Characteristics impacting performance • High velocity software release • Shared services • Cloud infrastructure (Variable platform capacity)
  • 10. Contrast old vs new SDLC paradigm Application characteristics Old Paradigm New Paradigm Software release frequency, Software component change frequency +----+----+----+---- Every quarter ++++++++++++ Continuous Shared services Minimal, predictable demand Extensive, unpredictable demand Platform capacity Fixed CPU, dedicated h/w Variable CPU, cloud implementation
  • 11. Shared services – explained 1 of 5
  • 12. Shared services – explained 2 of 5
  • 13. Shared services – explained 3 of 5
  • 14. Shared services – explained 4 of 5
  • 15. Shared services – explained 5 of 5 • Imagine 5, 10, or 50 applications concurrently running. • It becomes hard to predict the demand on shared services.
  • 16. Platform capacity contrast Application characteristics Old Paradigm New Paradigm Software release frequency, Software component change frequency +----+----+----+---- Every quarter ++++++++++++ Continuous Shared services Minimal, predictable demand Extensive, unpredictable demand Platform capacity Fixed CPU, dedicated h/w Variable CPU, cloud implementation
  • 17. Does pre-release testing mitigate new paradigm risk? Application characteristics New Paradigm Addressed by Pre-Release testing? Software release frequency, Software component change frequency ++++++++++++ Continuous No. Code your dependent upon is changing between you’re releases Shared services Extensive, unpredictable demand No. Doesn’t cover impact of other apps on shared resources Platform capacity Variable, cloud implementation No. Doesn’t expose under allocation of Production CPU
  • 18. How do we mitigate the new risk? AUGMENT PRE-PRELEASE TESTING WITH MONITORING. • Monitoring, most importantly performance monitoring, can mitigate performance risk associated with the new paradigm.
  • 19. How does monitoring mitigate these new risks? Application characteristics New Paradigm Risk Mitigation via Monitoring Software release frequency, Software component change frequency ++++++++++++ Continuous Provide immediate feedback when a s/w change has impacted a component. Shared services Extensive, unpredictable demand Demand patterns on all services are observed, and can be managed. Platform capacity Variable, cloud implementation Metrics used to prevent application starvation of CPU/Memory/Disk/ Network
  • 20. What are the limitations of monitoring? • Monitoring doesn’t remove performance risks like Pre-Release testing. • Reactive vs proactive. • It’s the best approach I can think of.
  • 21. How does Production monitoring reduce risk? • Prevent performance issues from entering production (when monitoring tools are used with Pre-Release testing) • Early detection/remediation of performance issues, before the customer notices. • Fast resolution of performance issues reported by customers. • Visibility for Operations
  • 22. Big picture review
  • 23. Production monitoring use case • Customers are complaining the web site is too slow. • Where is the problem? How does IT respond? Assemble a team of experts from each tier (bad) VS Monitored metrics immediately identify the broken tier (good).
  • 24. Production monitoring use case • Figuring out where the problem is located is 80% of the effort. • Performance monitoring does this work for us. That’s why its valuable!
  • 25. Production monitoring use case • Diagnostic strategy: • First isolate problem tier: left to right ↔ ; • than isolate problem layer within the tier: up and down ↕
  • 26. What metrics do we measure? Performance (business) metrics for tier isolation most important, hardest to capture • Transaction response times • Transaction rates • Error rates Resource metrics for layer isolation • CPU • Memory • etc… VM metrics Production monitoring use case
  • 27. What does monitoring look like? ● Target of test – An email notification system, multiple services orchestrated into a product. ● Performance dashboard examples from a test run. ● Performance dashboard examples from production.
  • 28. SUT - an email notification system
  • 29. Dashboard examples from a test run • Healthy service • Unhealthy service • Unhealthy service tier isolation
  • 30. Composite Transaction B
  • 31. Healthy dashboard example from a test
  • 32. Unhealthy dashboard example from a test
  • 33. Tier isolation of the performance problem
  • 34. Composite Transaction B
  • 35. Dashboard examples from production • Dashboard 1: How is the PDF rendering service performing? • Dashboard 2: Is Production email being delivered within SLA’s?
  • 36. How is the PDF rendering service performing?
  • 37. Is Production email being delivered within SLA’s?
  • 38. What does monitoring look like? • We looked at performance dashboards for • a healthy test • an unhealthy test • unhealthy tier isolation • production
  • 39. Performance metrics are hard to come by Presentation to date assumes you got’em If you aren’t collecting them already… ...its a big task to get them. • Buy vs build
  • 40. Takeaways ► Best practice for making this real in your shop
  • 41. Performance MONITORING in your company • Stick - Require dashboards for production release • Carrot - Provide easily adapted dashboard template All dashboards based on same three key metrics Build enterprise infrastructure to support templates • Project owners could use them as is or customize • Little burden means minimal resistance
  • 42. A generic performance dashboard.
  • 43. How do you implement Performance ASSURANCE • Prior to production release, the following performance requirements would need to be satisfied. • Pre-release Testing • Peak period scenario • Ramp up to first bottleneck test • Performance Monitoring dashboards • Lets talk about Pre-release testing, the other arrow in our quiver.
  • 44. Requirements - Pre-Release Testing • Peak period scenario • Stakeholder provides SLA for peak production demand • Performance test simulates peak production demand while human users exercise the system to confirm acceptable user experience • PASS is given when SLA is met OR stakeholders accept results.
  • 45. • Ramp up to first bottleneck test • Load is ramped up until the first significant bottleneck is found. • Useful for Ops to anticipate performance issues in production. • Provide information for the biz to create formal SLA’s. Requirements - Pre-Release Testing
  • 46. • Performance Monitoring dashboards • Performance monitoring is operational • Resource monitoring is operational • VM monitoring is operational Requirements - Performance Monitoring Dashboards
  • 47. • Dashboards available in both Pre-PROD and PROD environments • Pre-PROD coverage provides feedback in Pre-Release testing. • Pre-PROD coverage provides a testing ground for prod coverage. • Getting the right coverage will take practice. Requirements - Performance Monitoring Dashboards
  • 48. • Prior to production release, the following performance requirements would need to be satisfied. • Pre-release Testing • Peak period scenario • Ramp up to first bottleneck test • Performance Monitoring dashboards How do you implement Performance ASSURANCE
  • 49. • We talked about two techniques of mitigating risk. • Pre-Release testing • Monitoring • In practice, how does this theory map to performance problems? • My experience says → Mitigating performance risk
  • 50. Questions • Whew!! A lot of information
  • 51. Obbie Pet Sr Performance Engineer Ticketmaster.com Internet ticketing space 10+ years Ticketmaster Blog: http://tech.ticketmaster.com/ Contact: ObbiePet@ticketmaster.com or opet@qastrategy.com
  • 52. APPENDIX
  • 53. Example of a Resource monitor (Open TSDB)
  • 54. Performance is important ● Latency matters. Amazon found every 100ms of latency cost them 1% in sales. Google found an extra .5 seconds in search page generation time dropped traffic by 20%. --http://blog.gigaspaces.com/amazon-found-every-100ms-of-latency-cost-them-1-in-sales/
  • 55. Platform capacity– explained 1 of 6
  • 56. Platform capacity– explained 2 of 6
  • 57. Platform capacity– explained 3 of 6
  • 58. Platform capacity– explained 4 of 6
  • 59. Platform capacity– explained 5 of 6 The VM/Cloud problem.
  • 60. Platform capacity– explained 6 of 6
  • 61. Example of a performance log file used by Kibana to generate performance metrics: • • datetime="2013-12-12 11:59:59,538" severity="INFO " host="app6.template.jetcap1.coresys.tmcs" service_version="" client_host="10.72.4.75" client_version="" Correlation- ID="ab72d037-6362-11e3-80a4-f5667a7a5c6b" rid="" sid="" thread="Camel (337-camel-88) thread #42 - ServiceResolver" category="com.ticketmaster.platform.bam.strategies.Performa nceBAMStrategy" datetime="2013-12-12T11:59:59.538-08:00" bam="perf" dur="724" activity="template-call" camelhttppath="/template-notify-composite/rest/template- notify"
  • 62. Performance monitoring - Technologies • Selecting an appropriate monitoring technology is highly dependant on your specific environment. Below I share the classes of monitoring technologies to consider for your solution. BUILD IT: Custom code needed to collect metrics, open source leveraged for metric storage, BUILD IT: Custom code needed to collect metrics, open source leveraged for metric storage, analysis and reportingnd reporting SysLog harvesting, custom code is used to push performance data to SysLogs, which are than digested by log analyzers. (Kibana, Splunk) Tcollector agents, performance information is pushed to a time series database (OpenTSDB) BUY IT: End-2-End vendor monitoring solutions Network sniffers Network monitors or sniffer (OpNet) Stitching agent deployment required, piecing together transaction parts from header info Transaction marking agent deployment required, insert and then track headers JVM monitors agent deployment usually required (Dynatrace, AppDynamics)
  • 63. E2E Monitoring tool vendors: • BlueStripe http://bluestripe.com/ • Op-Tier http://www.optier.com/ • AppDynamics http://www.appdynamics.com/ • Dynatrace • http://www.compuware.com/application-performance- management/dynatrace-enterprise.html • Gartner group does a nice evaluation of this tool space
  • 64. E2E Transaction monitor example: