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dc.contributor.authorHamadanian, Pouya
dc.contributor.authorArzani, Behnaz
dc.contributor.authorFouladi, Sadjad
dc.contributor.authorKakarla, Siva Kesava Reddy
dc.contributor.authorFonseca, Rodrigo
dc.contributor.authorBillor, Denizcan
dc.contributor.authorCheema, Ahmad
dc.contributor.authorNkposong, Edet
dc.contributor.authorChandra, Ranveer
dc.date.accessioned2023-12-13T20:19:56Z
dc.date.available2023-12-13T20:19:56Z
dc.date.issued2023-11-28
dc.identifier.isbn979-8-4007-0415-4
dc.identifier.urihttps://hdl.handle.net/1721.1/153154
dc.description.abstractWe discuss the potential improvement large language models (LLM) can provide in incident management and how they can overhaul the ways operators conduct incident management today. We propose a holistic framework for building an AI helper for incident management and discuss the several avenues of future research needed to achieve it. We thoroughly analyze the fundamental requirements the community should consider when designing such helpers. Our work is based on discussions with operators of a large public cloud provider and their prior experiences both in incident management and with attempts to improve the incident management experience through various forms of automation.en_US
dc.publisherACM|The 22nd ACM Workshop on Hot Topics in Networksen_US
dc.relation.isversionofhttps://doi.org/10.1145/3626111.3628176en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alikeen_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/en_US
dc.sourceAssociation for Computing Machineryen_US
dc.titleA Holistic View of AI-driven Network Incident Managementen_US
dc.typeArticleen_US
dc.identifier.citationHamadanian, Pouya, Arzani, Behnaz, Fouladi, Sadjad, Kakarla, Siva Kesava Reddy, Fonseca, Rodrigo et al. 2023. "A Holistic View of AI-driven Network Incident Management."
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2023-12-01T08:49:52Z
dc.language.rfc3066en
dc.rights.holderThe author(s)
dspace.date.submission2023-12-01T08:49:53Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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