自动推荐云服务监控配置，减少人工失误和冗余告警。
A Holistic Framework for Automated Configuration Recommendation for Cloud Service Monitoring
- 基于服务图结构分析，模块化推荐最优监控配置。
- 在微软生产环境验证，显著提升配置相关性和覆盖率。
- 适合云运维团队和可靠性工程师快速部署监控体系。
大规模云服务的可靠性对用户满意度和业务连续性至关重要。尽管投入大量资源进行可靠性工程，生产事故仍不可避免，常导致客户影响和运营负担。大型云公司需在多个区域部署多种服务，依赖稳健的健康监控系统。然而当前监控配置过程以手动为主，多为被动且临时应对，造成覆盖盲区与告警重复。本文基于微软内部实践，全面研究监控创建流程，识别关键环节。进一步设计了一种模块化推荐框架，通过处理图结构的服务实体，生成最优监控配置建议。通过历史数据实验及对微软生产服务的用户研究，验证了该方法在提供相关配置建议方面的有效性。
原文摘要 · Abstract (English)
Reliability of large-scale cloud services is critical for user satisfaction and business continuity. Despite significant investments in reliability engineering, production incidents remain inevitable, often leading to customer impact and operational overhead. In large cloud companies, multiple services are deployed across regions necessitating robust health monitoring systems. However, the current monitor configuration process is manual, largely reactive and ad hoc, resulting in gaps in coverage and redundant alerts. In this paper, we present a comprehensive study of monitor creation in Microsoft, identifying key components in the existing process. We further design a modular recommendation framework that processes the graph structured service entities to suggest optimal monitor configurations. Through extensive experimentation on historical data and user study of recommendations for production services at Microsoft, we demonstrate the efficacy of our approach in providing relevant recommendations for monitor configurations.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。