Performance test on Carrefour
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The document discusses a performance testing stack consisting of Gatling and Jenkins. Gatling is an open source load testing tool built on Scala that uses Akka and Netty frameworks. It is capable of supporting high loads without degradation. Jenkins is an open source automation server used to schedule and collect feedback from Gatling tests. The document also provides examples of charts produced by Gatling to analyze test results, including response times and number of active users over time.
Performance test on Carrefour
- 1. Carrefour Performance Test Stack Denis Santos / Solution Architect November 2016
- 2. Stack ● Gatling is an open source performance testing solution in Scala programming language, that use Akka and Netty frameworks. ● Gatling is capable of supporting high simultaneous load without any degradation and avoiding the user response times. ● Gatling has a very light profile in terms of JVM performance. As smaller GC pauses are less than 0.075s with stack size less than 450 MB. So, based on that, we get a benchmark capability, while supporting 20k users in a 4GB JVM.
- 3. Stack ● Jenkins is an open source automation server. With Jenkins, organizations can accelerate the software development process through automation. Jenkins manages and controls development lifecycle processes of all kinds, including build, document, test, package, stage, deployment, static analysis and many more ● We using to schedule the execution and collect the feedback after the execution
- 4. Scenarios 50% Navigation Home Sub Cat. Category Search List of Prod. Product 20% Cart Navigation Add 2 products Cart Mofify Cart User Register Login 30% Product Page Product add 1 product Cart Modify Cart User Register Login
- 5. Results - Global Information This chart shows how response times are distributed among standard ranges. The right panel show number of OK/KO requests.
- 6. Results - Range per HTTP Status Code This chart shows how response times are distributed among standard ranges. The right panel show number of OK/KO requests.
- 7. Results - Active users over time This chart displays the active users during the simulation: total and per scenario.
- 8. Results - Response time distribution This chart displays the distribution of the response times.
- 9. Results - Response time percentiles over time This charts displays a variety of response time percentiles over time, but only for successful requests. As failed requests can end prematurely or be caused by timeouts, they would have a drastic effect on the percentiles computation.
- 10. Results - Requests per second over time This chart displays the number of requests sent per second over time.
- 11. Results - Responses per second over time This chart displays the number of responses received per second over time : total, successes and failures.