Anomalies in Microservice Architecture (train-ticket) based on version configurations
Monika Steidl · Zenodo (CERN European Organization for Nuclear Research) · 2022
The work contains ten datasets containing monitoring data (logs, Jaeger Traces and Prometheus KPI data). The datasets contain monitoring data from train-ticket, a benchmark system for microservices. The dataset includes a short description with explanations of identified anomalies. The structure of the folder is as follows: _ _ _ Each folder stores the respective data: Logs: original log file: LOGS_ _ _ .txt parsed log files required for Loglizer (anomaly detection technique): LOGS_ _ _ .txt_structured.csv LOGS_ _ _ .txt_templates.csv KPI Data: Monitoring_ _ _ Traces: Traces_ _ _