Anomalies in Microservice Architecture (train-ticket) based on version configurations

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:

<changed-microservice>_<third-party-library>_<version>_<date-when-data-was-collected>

Each folder stores the respective data:

1. Logs:
   • original log file: LOGS_<change-microservice>_<third-party-library>_<Version>.txt
   • parsed log files required for Loglizer (anomaly detection technique):
     • LOGS_<change-microservice>_<third-party-library>_<Version>.txt_structured.csv
     • LOGS_<change-microservice>_<third-party-library>_<Version>.txt_templates.csv
2. KPI Data: Monitoring_<change-microservice>_<third-party-library>_<Version>
3. Traces: Traces_<change-microservice>_<third-party-library>_<Version>