Towards establishing causality between change and incident
| Autor: | Larisa Shwartz, Amit Paradkar, Karin Murthy, Sinem Guven |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
business.industry
Computer science Data classification 02 engineering and technology Computer security computer.software_genre Causality 03 medical and health sciences Problem management 0302 clinical medicine Documentation Risk analysis (engineering) Incident management 020204 information systems Common knowledge 0202 electrical engineering electronic engineering information engineering Leverage (statistics) sense organs skin and connective tissue diseases business computer Risk management 030215 immunology |
| Zdroj: | NOMS |
| Popis: | It is common knowledge in the IT service domain that changes to the system configuration are responsible for a major portion of incidents that result in client outages. However, it is typically very difficult to establish a relationship between changes and incidents as proper documentation takes lower priority at change creation time, as well as during incident management, in order to deal with the tremendous time pressure to quickly implement changes and resolve incidents. As a result, it is often not possible to leverage historical data to perform retrospective analysis to identify any emerging trends linking changes to incidents, or to build predictive models for proactive incident prevention at change creation time. In this paper, we present an approach for establishing causality between changes and incidents through an ensemble of statistics, data classification, and natural language processing techniques. We demonstrate our approach with a real world example. |
| Databáze: | OpenAIRE |
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