{"title":"Examining Intelligent Failure Detection Models Using Metric Logs and Machine Learning in a Cloud Environment","authors":"Junho Lee, Jae-Pyo Park","doi":"10.5762/kais.2024.25.1.773","DOIUrl":null,"url":null,"abstract":"This paper describes the process of building and optimizing a machine learning model using server metric logs to predict game service failures. Of 334 servers in operation for the game service, 29 logs were utilized","PeriodicalId":112431,"journal":{"name":"Journal of the Korea Academia-Industrial cooperation Society","volume":"109 2","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Korea Academia-Industrial cooperation Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5762/kais.2024.25.1.773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper describes the process of building and optimizing a machine learning model using server metric logs to predict game service failures. Of 334 servers in operation for the game service, 29 logs were utilized