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Knowledge Acquisition for Automation in IT Infrastructure Support

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Mining Intelligence and Knowledge Exploration

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8891))

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Abstract

In todays IT-driven world, the IT Infrastructure Support (ITIS) unit aims for effective and efficient management of IT infrastructure of large and modern organizations. Automatic issue resolution is crucial for operational efficiency and agility of ITIS. For manually creating such automatic issue resolution processes, a Subject Matter Expert (SME) is required. Our focus is on acquiring SME knowledge for automation. Additionally, the number of distinct issues is large and resolution of issue instances requires repetitive application of resolver knowledge. Operational logs generated from the resolution process of issues, is resolver knowledge available in tangible form.

We identify functional blocks from the operational logs, as potential standard operators, which the SME will validate and approve. We algorithmically consolidate all the steps the resolvers have performed historically during the resolution process for a particular issue, and present to the SME a graphical view of the consolidation for his assessment and approval. We transform the graphical view into a set of rules along with the associated standard operators and finally ensemble them into a parametrized service operation in tool agnostic language. For an ITIS automation system, it is transformed into a configuration file of a targeted orchestrator tool. Bash and powershell script transformations of service operations are executed by resolvers manually or via an automation web portal.

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© 2014 Springer International Publishing Switzerland

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Chougule, S., Dhat, T., Deshmukh, V., Kelkar, R. (2014). Knowledge Acquisition for Automation in IT Infrastructure Support. In: Prasath, R., O’Reilly, P., Kathirvalavakumar, T. (eds) Mining Intelligence and Knowledge Exploration. Lecture Notes in Computer Science(), vol 8891. Springer, Cham. https://doi.org/10.1007/978-3-319-13817-6_34

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  • DOI: https://doi.org/10.1007/978-3-319-13817-6_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13816-9

  • Online ISBN: 978-3-319-13817-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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