Applications of arti fi cial intelligence for meeting network management challenges in the 1990s, IEEE GLOBECOM 1989. ɾಛఆͷαʔϏεΛαϙʔτ͢ΔͨΊͷωοτϫʔΫͷॳظઃܭ ɾηϯτϥϧΦϑΟεؒͷઓज़తͳઃඋܭը ɾεΠον͔Βͷϝοηʔδͷࢹͱஅ [Notaro 2021]: Notaro P, et al., A Survey of AIOps Methods for Failure Management. ACM TIST, 2021. ɾ1990ॳ಄͔ΒΦϯϥΠϯͷιϑτΣΞϋʔυΣΞͷނো༧ Ϟσϧ͕͍͔ͭ͘ఏҊ͞Ε͍ͯΔɽͦͷଞͷނোࢭํ๏ͳͲಉ࣌ظ [Cebulka 1989] [Notaro 2021]
G. "A Systematic Mapping Study in AIOps.” ICSOC. Springer, Cham, 2020. [Notaro ’20]: Fig.2 Taxonomy of AIOps as observed in the identified contributions ΑΓసࡌ োཧʹؔ͢Δݚڀ ϦιʔεͷׂͳͲͷ ࠷దԽʹؔ͢Δݚڀ
G. "A Systematic Mapping Study in AIOps.” ICSOC. Springer, Cham, 2020. ɾAIOpsؔ࿈ͷจɿ670 ɾ670݅ͷ62.1%͕Failure Managementʢোཧʣʹؔ࿈͍ͯ͠Δ ɾো༧ଌʢ26.4ˋʣোݕग़ʢ33.7ˋʣݪҼੳʢ26.7ˋʣ จ૿Ճ
A Survey of AIOps Methods for Failure Management. ACM Transactions on Intelligent Systems and Technology (TIST). 2021 Nov 30;12(6):1-45. Lyu Y, Rajbahadur GK, Lin D, Chen B, Jiang ZM. Towards a Consistent Interpretation of AIOps Models. ACM Transactions on Software Engineering and Methodology (TOSEM). 2021 Nov 15;31(1):1-38. Soldani J, Brogi A. Anomaly detection and failure root cause analysis in (micro) service-based cloud applications: A survey. ACM Computing Surveys (CSUR). 2022 Feb 3;55(3):1-39. https://blog.yuuk.io/entry/2020/ieeecloud2020 https://netman.aiops.org/publications/ ਗ਼՚େֶ NETMAN LAB ࠃࡍձٞ IEEE CLOUD AIOpsؔ࿈ͷαʔϕΠจ
L, Yang X, Li S, Zhang M, Jin X, Wen X, Nie X, Zhang W, Sui K. Identifying Root-Cause Metrics for Incident Diagnosis in Online Service Systems. [PatternMatcher 2021] 30ఔͷظؒͷղੳͰΑ͍ͨΊɺقઅੑϦϦʔεʹΑΔਖ਼ৗ ϞʔυͷมԽΛߟྀ͠ͳͯ͘Α͍ɻ ͢Ͱʹোݕग़͞ΕͨޙͳͷͰɺΦϑϥΠϯҟৗݕͰΑ͍
Li S, Zhang M, Jin X, Wen X, Nie X, Zhang W, Sui K. Identifying Root-Cause Metrics for Incident Diagnosis in Online Service Systems. 24 ඪຊXͱඪຊY͕ಉҰͷूஂͷΑΓੜ͍ͯ͡ Δ͔Λݕఆ͢Δ 2ඪຊؒͷͷࠩΛΈΔݕఆɿK-Sݕఆ ͏·͍͔͘ͳ͔ͬͨέʔε ɾγϣʔτεύΠΫͷΑ͏ͳݦஶͳ֎ΕΛؚΉ ࣌ܥྻ p: 0.11 p: 0.51 ɾগͷ֎ΕͰɺ͕ҧ͏ͱΈͳ͞ΕΔ΄ ͲͰͳ͍ ࣌ܥྻΛ௨ৗظؒͱςετظؒʹ2ׂ͠ɺظؒؒ ͷࠩҟΛݕఆ ʢ[PatternMatcher 2021]Ͱ࠾༻͞Ε͍ͯΔʣ