Anomaly Detection im Monitoring des Produktivbetriebs der ODAV AG anhand der Analyse der Error-Count Metrik

Benjamin Eder; Benjamin Neumann; Frank Herrmann

Anomaly detection in the monitoring of the productive operation of ODAV AG based on the analysis of the error count metric

Authors

Benjamin Eder (M.Sc.) ODAV AG, Gesellschaft für Informatik und Telekommunikation
Benjamin Neumann (Dipl.-Inf. (FH)) ODAV AG, Gesellschaft für Informatik und Telekommunikation
Prof. Dr. Frank Herrmann Ostbayerische Technische Hochschule Regensburg

Keywords:

Anomaly Detection, Machine Learning

Abstract

Many companies develop software and at the same time provide it to the customer on servers.
Since it is necessary that the operation of the software is guaranteed 24 hours a day seven days a week, a system is to be developed that automatically detects anomalies in the operation of the servers and report this to the appropriate such as the operating data center.