Online Detection of Operator Errors in Cloud Computing Using Anti-patterns

  • Arthur VetterEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 340)


IT services are subject of several maintenance operations like upgrades, reconfigurations or redeployments. Monitoring those changes is crucial to detect operator errors, which are a main source of service failures. Another challenge, which exacerbates operator errors is the increasing frequency of changes, e.g. because of continuous deployments like often performed in cloud computing. In this paper, we propose a monitoring approach to detect operator errors online in real-time by using complex event processing and anti-patterns. The basis of the monitoring approach is a novel business process modelling method, combining TOSCA and Petri nets. This model is used to derive pattern instances, which are input for a complex event processing engine in order to analyze them against the generated events of the monitored applications.


Complex event processing Anti-pattern TOSCA IT service management Anomaly detection 


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Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Horus software GmbHEttlingenGermany

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