Mateusz Gruszczynski - Performance tests in Gatling (Quality Questions Conference)
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Performance tests in Gatling outlines how to use the Gatling load testing tool to test the performance of web applications. Gatling allows writing simulations in Scala to generate load and analyze results. It uses an asynchronous actor model and handles a high number of concurrent users without blocking. The document discusses setting goals for performance tests, using Gatling's GUI to record and replay tests, analyzing results like response times and errors, and validating responses with assertions in the Scala simulations. Code examples demonstrate configuring requests, storing data in sessions, handling responses, and using loops and conditions to model different user behaviors in tests.
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Mateusz Gruszczynski - Performance tests in Gatling (Quality Questions Conference)
- 1. Performance tests in Gatling Mateusz Gruszczyński, Grand Prade mateusz.gruszczynski@grandparade.co.uk
- 2. Performance Testing ● Why we should test performance? ● What are performance tests? – Performance – Load – Stress – Soak – Capacity
- 3. How to test performance ● Functional vs Non-Functional approach ● Setting goals ● Good practices ● Understanding architecture and tech stack ● Analyzing results
- 4. Why Gatling? ● Asynchronous ● Actor model ● Non blocking I/O ● Simple configuration ● GUI and DSL ● Easy to understand code ● Extendable
- 6. HTTP & REST ● Request methods – GET, POST, PUT, PATCH, DELETE ... ● Headers ● HTTP Codes – 200, 201, 400, 401, 402, 422, 500 ● Session ● Authentication ● REST
- 7. Gatling GUI ● Works as proxy server ● Allows to record requests ● Generates simulation code ● No coding required ● Allows to replay recorded simulations ● Generates reports
- 9. Simulation Report ● Summary and per request reports ● Multiple metrics ● Time distribution ● Detailed statistics
- 10. Lets look at some code ● Simulations are written in Scala ● Simulations use Gatling DSL to configure requests ● Simulation is a set of scenarios ● Generated requests are very simple ● Generated code is messy ● Complex logic can (should) be added to scenario
- 11. Basic Gatling DSL elements ● Requests ● Checkers ● Assertions ● Loops ● Condition Blocks ● more: Cheat sheet
- 13. Writing first request ● Setting simple GET request ● Validating response code ● Validation response content – HTML response – JSON response ● Configuring assertions and success conditions
- 14. We need more users! ● Injecting users ● Injection strategies – atOnceUsers – rampUsers – constantUsersPerSec – rampUsersPerSec – mixed strategies ● Injection strategies vs request per second ● Throttling
- 15. Gatling Session ● Storing data in session ● Reusing stored data in scenarios ● Filling placeholders ● Coding inside session context (block)
- 16. Configuring request parameters ● URL – base URL – URL params ● Headers – content type – authorization ● Resources
- 17. Passing request data ● StringBody ● RawFileBody ● Constructing data based on session
- 18. Checking response ● Status ● Content – HTML – JSONPath ● Headers ● Response Time
- 19. Writing global assertions ● Max time ● Average time ● Percentiles ● Detail
- 20. Loops and conditions ● Conditions – doIf ... – doSwitch – randomSwitch – etc. ● Failure conditions – tryMax – exitBlockOnFail – exitHereIfFailed ● Loops – forever – repaet – during – foreach – asLongAs
- 21. Loading data to simulation ● Feeder sources – Files ● CSV ... ● Json – Remote files – Databases ● JDBC ● Redis ● Feeder strategies – queue – shuffle – random – circular
- 22. Advanced reporting & monitoring ● LogBack ● JSON Stats ● ExtraInfoExtractor ● Live monitoring – Graphite – InfluxDB
- 23. Questions?