高技术通讯2025，Vol.35Issue(6)：604-612,9.DOI:10.3772/j.issn.1002-0470.2025.06.004
基于Graphormer的时空间多源数据微服务故障定位算法
A Graphormer-based spatial-temporal and multi-source data algorithm for microservices' fault localization
摘要
Abstract
Fault localization in microservices scenarios plays a crucial role in improving the efficiency of data centers and cloud computing,as well as safeguarding user service quality.However,existing fault localization methods only an-alyze a single type of data,making it challenging to find suitable methods that consider multiple types of data.Mo-reover,algorithms based on graph data often analyze relationships between services with direct or indirect invoca-tion,neglecting the issue of physical resource competition between microservices that are not dependent on each other.To address this issue,we propose a Graphormer-based temporal analysis(GTA)for joint fault diagnosis using multi-type spatial and temporal data.Compared with existing algorithms,we successfully utilize Graphormer to analyze all observable data from microservices,including logs,metrics,and traces.By constructing spatial ma-trices based on invocation chain dependency information and building temporal feature vectors from microservices'performance metrics and log information,we simultaneously capture critical information from spatial and temporal dimensions.Experimental results on a real bank's microservices system and two open-source platforms show GTA's superiority,with a predictive error reduction of at least 15％compared to the latest methods.关键词
云计算/微服务/时空预测/Graphormer/服务质量Key words
cloud computing/microservice/spatial-temporal prediction/Graphormer/quality of service(QoS)引用本文复制引用
任锐,王阳,关洪涛,谢高岗..基于Graphormer的时空间多源数据微服务故障定位算法[J].高技术通讯,2025,35(6):604-612,9.基金项目
国家重点基础研究发展计划(2022YFB3103000)资助项目. （2022YFB3103000）
