Gatling Framework
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A Gatling Framework is an open-source load and performance testing framework.
- See: ThoughtWorks, Gatling-gRPC, Scala (Programming Language), Load Testing, Software Performance Testing.
References
2020
- (Wikipedia, 2020) ⇒ https://en.wikipedia.org/wiki/Gatling_(software) Retrieved:2020-7-15.
- Gatling is an open-source load and performance testing framework based on Scala, Akka and Netty. The first stable release was published on January 13, 2012. In 2015, Gatling's founder, Stéphane Landelle, created a company (named "Gatling Corp"), dedicated to the development of the open-source project. According to Gatling Corp's official blog, Gatling was downloaded more than 800,000 times (August 2017). In June 2016, Gatling officially presented Gatling FrontLine, Gatling's Enterprise Version with additional features. The software is designed to be used as a load testing tool for analyzing and measuring the performance of a variety of services, with a focus on web applications. Gatling was mentioned twice in ThoughtWorks Technology Radar, in 2013 and 2014, "as a tool worth trying", with an emphasis on "the interesting premise of treating your performance tests as production code".
The latest stable release is Gatling 3.1.3. It was published on June 24, 2019.
- Gatling is an open-source load and performance testing framework based on Scala, Akka and Netty. The first stable release was published on January 13, 2012. In 2015, Gatling's founder, Stéphane Landelle, created a company (named "Gatling Corp"), dedicated to the development of the open-source project. According to Gatling Corp's official blog, Gatling was downloaded more than 800,000 times (August 2017). In June 2016, Gatling officially presented Gatling FrontLine, Gatling's Enterprise Version with additional features. The software is designed to be used as a load testing tool for analyzing and measuring the performance of a variety of services, with a focus on web applications. Gatling was mentioned twice in ThoughtWorks Technology Radar, in 2013 and 2014, "as a tool worth trying", with an emphasis on "the interesting premise of treating your performance tests as production code".