{"title":"检验云环境中使用度量日志和机器学习的智能故障检测模型","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":"{\"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}","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}
Examining Intelligent Failure Detection Models Using Metric Logs and Machine Learning in a Cloud Environment
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
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