Identifying Performance Issues in Microservice Architectures through Causal Reasoning

Evaluating the performance of Microservices Architectures (MSA) is essential to ensure their proper functioning and meet end-user satisfaction. For MSA performance analysts, one of the most challenging tasks is to determine the cause of any deviation of relevant metrics from the specified range.We introduce CAR-PT (CAusal-Reasoning-driven Performance Testing), a model-based technique for workload generation designed for the performance testing of MSA. CAR-PT leverages causal reasoning to effectively explore the space of operational conditions, with the goal of identifying those that lead to performance issues. Preliminary results show that CAR-PT is effective in generating configurations for discovering performance issues of an MSA.