Continuous performance: Load testing for developers with gatling @ JavaOne 2016
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The document discusses the importance of integrating continuous performance load testing within the development process using Gatling, highlighting that traditional performance testing is often inadequate. It emphasizes that performance tests should be conducted by development teams in alignment with unit and integration tests to ensure quick feedback and proactive issue identification. Key takeaways include the benefits of Gatling for load testing and the impact of frontend changes on backend performance.
Continuous performance: Load testing for developers with gatling @ JavaOne 2016
- 1. Continuous Performance Load testing for developers with Gatling Tim van Eijndhoven @TimvEijndhoventvaneijndhoven@jpoint.nl
- 2. @bjschrijver@TimvEijndhoven Let’s meet Tim van Eijndhoven
- 3. @bjschrijver@TimvEijndhoven Let’s meet Bert Jan Schrijver
- 4. @bjschrijver@TimvEijndhoven Outline • Performance testing process • Introduction to Gatling • Demo • Results • Looking forward • Summary • Q&A
- 5. @bjschrijver@TimvEijndhoven How it all started…
- 6. @bjschrijver@TimvEijndhoven Performance testing should be part of the process
- 7. @bjschrijver@TimvEijndhoven Performance testing traditionally… …happens several times per year …and/or at major releases …is performed by specialists .. which is far from ideal: - changes were made long ago - many different code changes - at a certain moment in time - when is a test required?
- 8. @bjschrijver@TimvEijndhoven Traditional performance testing design write code test code performance test release unit tests integration tests
- 9. @bjschrijver@TimvEijndhoven design write code test code release unit tests integration tests performance tests Performance testing in continuous delivery
- 10. @bjschrijver@TimvEijndhoven Continuous Delivery Demands code to be Always production ready Short feedback cycles Maintained by self-supporting teams In regard to performance Has to be under control Effects should be clear ASAP No external specialists
- 11. @bjschrijver@TimvEijndhoven Part of the process With the same level of support as - Unit tests and integration tests - Continuous Integration - Zero-downtime deployments Performed by the development team
- 12. @bjschrijver@TimvEijndhoven Performance testing process Design Record Operationalise Execute Report
- 13. @bjschrijver@TimvEijndhoven Designing scenarios Generic tests that test core functionality Specialised tests that test specific features in depth
- 14. @bjschrijver@TimvEijndhoven Tool support is key for performance test adoption
- 15. @bjschrijver@TimvEijndhoven Gatling package computerdatabase // 1 import io.gatling.core.Predef._ // 2 import io.gatling.http.Predef._ import scala.concurrent.duration._ class BasicSimulation extends Simulation { // 3 val httpConf = http // 4 .baseURL("http://computer-database.gatling.io") // 5 .acceptHeader("text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8") // 6 .doNotTrackHeader("1") .acceptLanguageHeader("en-US,en;q=0.5") .acceptEncodingHeader("gzip, deflate") .userAgentHeader("Mozilla/5.0 (Windows NT 5.1; rv:31.0) Gecko/20100101 Firefox/31.0") val scn = scenario("BasicSimulation") // 7 .exec(http("request_1") // 8 .get("/")) // 9 .pause(5) // 10 setUp( // 11 scn.inject(atOnceUsers(1)) // 12 ).protocols(httpConf) // 13 }
- 17. @bjschrijver@TimvEijndhoven Gatling core concepts Scenario Feeder A sequence of http requests used to simulate application usage A tool used to fill request parameters Recorder The tool used to record http requests or take a HAR-file and convert it to Gatling DSL Gatling DSL Easy-to-read, developer-friendly way of defining tests
- 19. @bjschrijver@TimvEijndhoven Scenario to outcome Browser HAR-file Gatling recorder DSL Custom changes DSL Gatling Report
- 20. @bjschrijver@TimvEijndhoven Re-record Front end Back end client / server interaction before change front-end code change Front end Back end client / server interaction after change
- 22. @bjschrijver@TimvEijndhoven Performance predicting trends - Automatically execute test at start and end of work day - Pushing test environment to the breaking point - Analyse average response time graph to see the trend
- 24. @bjschrijver@TimvEijndhoven Trend interpretations We can See how changes affect performance Have feedback on performance in short amount of time We cannot See which load the application can endure in production
- 25. @bjschrijver@TimvEijndhoven Results so far - Prevented multiple issues in production - Helped testing performance fixes and database tuning - Discovered configuration error in test infrastructure - Helped track down and validate a fix for a memory leak - Helped tweak database indexes - Made teams more aware of their product’s performance
- 26. @bjschrijver@TimvEijndhoven - Automate (re-)recording process - Re-use functional test scenarios as performance tests - Eliminate custom code changes Further development
- 28. @bjschrijver@TimvEijndhoven Some take-aways - Performance testing should be a first class citizen in your development cycle - Frontend changes can impact backend performance - Gatling is an awesome programmer friendly tool for load testing - The approach I shared monitors performance trends - it does NOT determine the maximum load a production environment can endure https://github.com/timve/continuous-performance-demo https://github.com/bertjan/gatling-seed
- 30. @bjschrijver@TimvEijndhoven Thanks for your time! Liked it? Tweet it!