The thesis focuses on performance testing of applications in a Kubernetes environment deployed on the AWS cloud. Firstly, the performance testing will be explained covering approaches, reasons and benefits of it for software applications. Subsequently, the tools required for testing, such as load generators and monitoring tools, will be analyzed. Their significance in the context of the overall performance testing process will also be given.

In the practical part, a framework for automated deployment of the testing infrastructure will be created. The framework will allow defining the configuration of the required computational resources and the ability to repeat deployments. The testing infrastructure will include a prepared Kubernetes cluster and the necessary tools. The testing will be conducted on the Kafka application, and the test results will be compared on two differently sized environments – the default and the doubled configuration – to analyze the scalability of the application. The test results will be processed and presented in the form of graphs, which will analyze the scalability efficiency of the application under different levels of load. The testing data will be generated to vary message size and their amount per second.