Optimization of Anomaly Detection in a Microservice System Through Continuous Feedback from Development
Monitoring a microservice system may bring a lot of benefits to development teams such as early detection of run-time errors and various performance anomalies. In this study, we explore deep learning (DL) solutions for detection of anomalous system's behavior based on collected monitoring data that consists of applications' and systems' performance metrics. The study is conducted in a collaboratio
