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.

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
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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.

12. Start with automation