{"id":"https://openalex.org/W7125900643","doi":"https://doi.org/10.1109/ase63991.2025.00263","title":"KAIOPS: A Platform Solution of End-to-End Multi-Modal AIOps for AI Training at Scale","display_name":"KAIOPS: A Platform Solution of End-to-End Multi-Modal AIOps for AI Training at Scale","publication_year":2025,"publication_date":"2025-11-16","ids":{"openalex":"https://openalex.org/W7125900643","doi":"https://doi.org/10.1109/ase63991.2025.00263"},"language":null,"primary_location":{"id":"doi:10.1109/ase63991.2025.00263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ase63991.2025.00263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5088632552","display_name":"Zeying Wang","orcid":"https://orcid.org/0000-0002-4215-3270"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zeying Wang","raw_affiliation_strings":["Beihang University"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108149924","display_name":"Junhong Liu","orcid":"https://orcid.org/0009-0000-5524-1395"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junhong Liu","raw_affiliation_strings":["Beihang University"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124133856","display_name":"Penghao Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108351","display_name":"Kushiro Rosai Hospital","ror":"https://ror.org/01s9rzk09","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210108351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Penghao Zhang","raw_affiliation_strings":["Kuaishou Inc"],"affiliations":[{"raw_affiliation_string":"Kuaishou Inc","institution_ids":["https://openalex.org/I4210108351"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124087119","display_name":"Xiaoyang Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I130828816","display_name":"University of Leeds","ror":"https://ror.org/024mrxd33","country_code":"GB","type":"education","lineage":["https://openalex.org/I130828816"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Xiaoyang Sun","raw_affiliation_strings":["University of Leeds"],"affiliations":[{"raw_affiliation_string":"University of Leeds","institution_ids":["https://openalex.org/I130828816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124056380","display_name":"Xu Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Wang","raw_affiliation_strings":["Beihang University"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066123431","display_name":"Tianyu Wo","orcid":"https://orcid.org/0000-0002-5331-3364"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyu Wo","raw_affiliation_strings":["Beihang University"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124128913","display_name":"Chunming Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunming Hu","raw_affiliation_strings":["Beihang University"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5088728073","display_name":"Chengru Song","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108351","display_name":"Kushiro Rosai Hospital","ror":"https://ror.org/01s9rzk09","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210108351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chengru Song","raw_affiliation_strings":["Kuaishou Inc"],"affiliations":[{"raw_affiliation_string":"Kuaishou Inc","institution_ids":["https://openalex.org/I4210108351"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124063272","display_name":"Jin Ouyang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210108351","display_name":"Kushiro Rosai Hospital","ror":"https://ror.org/01s9rzk09","country_code":"JP","type":"healthcare","lineage":["https://openalex.org/I4210108351"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jin Ouyang","raw_affiliation_strings":["Kuaishou Inc"],"affiliations":[{"raw_affiliation_string":"Kuaishou Inc","institution_ids":["https://openalex.org/I4210108351"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050796169","display_name":"Renyu Yang","orcid":"https://orcid.org/0000-0001-6334-4925"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Renyu Yang","raw_affiliation_strings":["Beihang University"],"affiliations":[{"raw_affiliation_string":"Beihang University","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":10,"corresponding_author_ids":["https://openalex.org/A5088632552"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.70905031,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3192","last_page":"3203"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.5485000014305115,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.5485000014305115,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.1444000005722046,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.04439999908208847,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/testbed","display_name":"Testbed","score":0.5856000185012817},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.570900022983551},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.507099986076355},{"id":"https://openalex.org/keywords/root-cause","display_name":"Root cause","score":0.45579999685287476},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.44369998574256897},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.41749998927116394},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.40070000290870667},{"id":"https://openalex.org/keywords/resilience","display_name":"Resilience (materials science)","score":0.39079999923706055}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6337000131607056},{"id":"https://openalex.org/C31395832","wikidata":"https://www.wikidata.org/wiki/Q1318674","display_name":"Testbed","level":2,"score":0.5856000185012817},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.570900022983551},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.507099986076355},{"id":"https://openalex.org/C84945661","wikidata":"https://www.wikidata.org/wiki/Q7366567","display_name":"Root cause","level":2,"score":0.45579999685287476},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.44369998574256897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41850000619888306},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.40070000290870667},{"id":"https://openalex.org/C2779585090","wikidata":"https://www.wikidata.org/wiki/Q3457762","display_name":"Resilience (materials science)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C130963320","wikidata":"https://www.wikidata.org/wiki/Q1401207","display_name":"Root cause analysis","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.36340001225471497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35109999775886536},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.34689998626708984},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.30390000343322754},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C171078966","wikidata":"https://www.wikidata.org/wiki/Q111029","display_name":"Root (linguistics)","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C63540848","wikidata":"https://www.wikidata.org/wiki/Q3140932","display_name":"Fault tolerance","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.267300009727478},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C115925183","wikidata":"https://www.wikidata.org/wiki/Q1412694","display_name":"Knowledge-based systems","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.258899986743927},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.25760000944137573},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ase63991.2025.00263","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ase63991.2025.00263","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 40th IEEE/ACM International Conference on Automated Software Engineering (ASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5906249284744263,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W861925310","https://openalex.org/W2023639956","https://openalex.org/W2118978333","https://openalex.org/W2963351448","https://openalex.org/W2965838158","https://openalex.org/W2966971704","https://openalex.org/W2970641574","https://openalex.org/W2985374077","https://openalex.org/W3005780259","https://openalex.org/W3022004659","https://openalex.org/W3083560262","https://openalex.org/W3092126302","https://openalex.org/W3099837301","https://openalex.org/W3100178186","https://openalex.org/W3155331679","https://openalex.org/W3161254931","https://openalex.org/W3184003041","https://openalex.org/W3194768773","https://openalex.org/W3198081460","https://openalex.org/W3199139386","https://openalex.org/W3210060313","https://openalex.org/W4200347562","https://openalex.org/W4226065059","https://openalex.org/W4286588841","https://openalex.org/W4291214045","https://openalex.org/W4294170691","https://openalex.org/W4312967612","https://openalex.org/W4380881139","https://openalex.org/W4382203537","https://openalex.org/W4384345623","https://openalex.org/W4385568016","https://openalex.org/W4386969744","https://openalex.org/W4388212563","https://openalex.org/W4388212671","https://openalex.org/W4388483274","https://openalex.org/W4389158453","https://openalex.org/W4391054939","https://openalex.org/W4396758707","https://openalex.org/W4400762160","https://openalex.org/W4402516174","https://openalex.org/W4404386172","https://openalex.org/W4404952936","https://openalex.org/W4404953115","https://openalex.org/W4406728997","https://openalex.org/W4409248832","https://openalex.org/W4413267884"],"related_works":[],"abstract_inverted_index":{"The":[0,139],"resilience":[1],"of":[2,27,106,182,194,212],"large-scale":[3,111],"AI":[4,12,28,112],"training":[5,30,75,113,188,225],"platforms":[6],"are":[7],"fundamental":[8],"to":[9,43,49,62,83,124],"enabling":[10],"contemporary":[11],"innovation":[13],"and":[14,25,53,68,77,87,103,127,131,166,173,207,217,226],"business":[15],"development.":[16],"However,":[17],"with":[18,213],"the":[19,23,34,38,64,88,150,180,191,219],"rapid":[20],"increase":[21],"in":[22,74,80,202,204],"scale":[24],"complexity":[26],"model":[29,141,224],"tasks,":[31,76],"anomalies":[32,102],"become":[33],"norm":[35],"rather":[36],"than":[37],"exception":[39],"at":[40,115],"scale.":[41],"Failing":[42],"handle":[44],"them":[45],"properly":[46],"may":[47],"lead":[48],"enormous":[50],"resource":[51],"waste":[52],"prolonged":[54],"development":[55],"cycles.":[56],"Traditional":[57],"anomaly":[58],"detection":[59,140,151],"methods":[60],"struggle":[61],"tackle":[63],"complex":[65],"temporal":[66,133],"characteristics":[67],"extreme":[69],"class":[70],"imbalance":[71],"inherently":[72],"manifesting":[73],"fall":[78],"short":[79],"automated":[81,97,169],"solution":[82,99,175],"root":[84,170],"cause":[85,171],"analysis":[86,172],"follow-up":[89],"remediation.":[90],"This":[91],"paper":[92],"proposes":[93],"KAIOPS,":[94],"an":[95],"end-to-end":[96,157],"platform":[98],"for":[100,110,148,168,222],"handling":[101],"engineering":[104],"experience":[105],"daily":[107],"operational":[108],"maintenance":[109],"clusters":[114],"Kuaishou.":[116],"KAIOPS":[117,161,198],"employs":[118],"a":[119,143,155],"Temporal":[120],"Context":[121],"Encoding":[122],"mechanism":[123],"precisely":[125],"capture":[126],"encode":[128],"long-term":[129],"trends":[130],"critical":[132],"context":[134],"information":[135],"within":[136],"fault":[137],"evolution.":[138],"elaborates":[142],"dynamic":[144],"class-weighted":[145],"loss":[146],"function":[147],"enhancing":[149],"performance.":[152],"To":[153],"deliver":[154],"complete":[156],"intelligent":[158],"processing":[159],"pipeline,":[160],"further":[162],"leverages":[163],"knowledge":[164],"graph":[165],"LLMs":[167],"actionable":[174],"generation.":[176],"Extensive":[177],"experiments,":[178],"on":[179],"basis":[181],"data":[183],"collected":[184],"from":[185],"Kuaishou\u2019s":[186],"production-grade":[187],"clusters,":[189],"show":[190],"superior":[192],"performance":[193],"our":[195],"proposed":[196],"approach.":[197],"has":[199],"been":[200],"deployed":[201],"Kuaishou,":[203],"both":[205],"testbed":[206],"production":[208],"grade":[209],"environments,":[210],"consisting":[211],"over":[214],"10,000":[215],"GPUs,":[216],"accelerate":[218],"reliability":[220],"assurance":[221],"industry-scale":[223],"serving.":[227]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-01-29T00:00:00"}
