Introduction: A lot of our performance tests are driven by gatling. When moving our tests to Google cloud, we face a lot of questions. One of them is how to manage the life cycle of the test. First, we need to generate the .csv file as the feeder to the gatling test. Second, we need to know when the test is finished. Third, we need to retrieve the results from the cloud. According to Distributed load testing with Gatling and Kubernetes , a Kubernetes Job should be used. While this blog provides good information, I still need to figure out how to create the feeder .csv and share it with gatling script. Using InitContainers to pre-populate Volume data in Kubernetes provides me another piece of information. In this blog post, I will show you my experiment of creating a Kubernetes job to drive performance workload with Gatling. Create Feeder script: My gatling script reads the feeder .csv (benchmark.csv). I have a python script generating the benchmark.csv file.