一句话：展示 AIOpsLab 开放平台，旨在应对 AIOps 研究中的基准测试、工作负载模拟与可复现性挑战。
随着 AI 的显著进展，面向云系统运维的 AI 智能体研究（AIOps）蓬勃发展。基于 AI 的故障检测、根因分析和故障缓解已成为热点，相关论文发表于 FSE、ICSE、ASE、ISSTA 等软件工程会议。然而，当前 AIOps 研究仍面临若干实践挑战，包括基准测试、工作负载模拟和可复现性。本文提出并展示 AIOpsLab，一个面向 AIOps 研究的开放平台，旨在为这些挑战提供统一基础设施。摘要未展开具体平台机制与评估结果，但强调该平台以开放、可复现的方式支持 AIOps 研究。
The significant advances in AI have been driving a blooming landscape of research on developing AI agents for various kinds of cloud system operations, which is often referred to as AIOps. For example, AI-based fault detection, root cause analysis, and failure mitigation have been a hot topic in recent years with many research papers published at Software Engineering conferences like FSE, ICSE, ASE, and ISSTA. However, AIOps research today faces major practical challenges such as benchmarking, workload simulation, and reproducibility.