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

Abstract : 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.
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Submitted on : Thursday, March 7, 2019 - 3:28:01 PM
Last modification on : Thursday, March 7, 2019 - 3:29:55 PM
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Arthur Vetter. Online Detection of Operator Errors in Cloud Computing Using Anti-patterns. 7th International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Dec 2017, Neuchatel, Switzerland. pp.1-24, ⟨10.1007/978-3-030-11638-5_1⟩. ⟨hal-02060694⟩

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