LO2: Microservice API Anomaly Dataset of Logs and Metrics
Alexander Bakhtin, Jesse Nyyssölä, Yuqing Wang, Noman Ahmad, Ke Ping, Matteo Esposito, Mika Mäntylä, Davide Taibi · 2025
Context. Microservice-based systems have gained significant attention over the past years. A critical factor for understanding and analyzing the behavior of these systems is the collection of monitoring data such as logs, metrics, and traces. These data modalities can be used for anomaly detection and root cause analysis of failures. In particular, multi-modal methods utilizing several types of this data at once have gained traction in the research community since these three modalities capture different dimensions of system behavior.