Automated Scalability Assessment in DevOps Environments

In this extended abstract, we provide an outline of the presentation planned for WOSP-C 2020. The goal of the presentation is to provide an overview of the challenges and approaches for automated scalability assessment in the context of DevOps and microservices. The focus of this presentation is on approaches that employ automated identification of performance problems because these approaches can leverage performance anti-pattern[5] detection technology. In addition, we envision extending the approach to recommend component refactoring. In our previous work[1,2] we have designed a methodology and associated tool support for the automated scalability assessment of micro-service architectures, which included the automation of all the steps required for scalability assessment. The presentation starts with an introduction to dependability, operational Profile Data, and DevOps. Specifically, we provide an overview of the state of the art in continuous performance monitoring technologies[4] that are used for obtaining operational profile data using APM tools. We then present an overview of selected approaches for production and performance testing based on the application monitoring tool (PPTAM) as introduced in [1,2]. The presentation concludes by outlining a vision for automated performance anti-pattern[5] detection. Specifically, we present the approach introduced for automated anti-pattern detection based on load testing results and profiling introduced in[6] and provide recommendations for future research.