arXiv:2501.08243cs.SEcs.AI2025-01中稿 · CAIN 2025被引 21

用多智能体框架让云运维自动执行复杂任务

Engineering LLM Powered Multi-agent Framework for Autonomous CloudOps

  • 设计多智能体系统,用生成式AI协调不同任务
  • 在真实运维中提升准确率与响应速度
  • 适合需要自动化云管理的企业用户

云运维(CloudOps)是自动化管理与优化云基础设施的快速发展的领域,对应对日益复杂的云环境至关重要。蒙蒂云公司(MontyCloud Inc.)在该领域领先,利用自主机器人处理云合规、安全与持续运营。为提升平台可用性与效率,我们引入生成式AI构建基于GenAI的自治云运维解决方案。面对多元数据源、多流程编排及复杂工作流等挑战,我们开发了MOYA多智能体框架,融合生成式AI与必要的人机协同控制。该框架集成内外部系统,在任务编排、安全性与错误缓解方面优化,通过检索增强生成(RAG)实现精准、可靠、相关的洞察输出。通过实践者评估与自动化检测,系统在复杂工作流中表现出比非智能体方法更高的准确性、响应性与有效性。

原文摘要 · Abstract (English)

Cloud Operations (CloudOps) is a rapidly growing field focused on the automated management and optimization of cloud infrastructure which is essential for organizations navigating increasingly complex cloud environments. MontyCloud Inc. is one of the major companies in the CloudOps domain that leverages autonomous bots to manage cloud compliance, security, and continuous operations. To make the platform more accessible and effective to the customers, we leveraged the use of GenAI. Developing a GenAI-based solution for autonomous CloudOps for the existing MontyCloud system presented us with various challenges such as i) diverse data sources; ii) orchestration of multiple processes; and iii) handling complex workflows to automate routine tasks. To this end, we developed MOYA, a multi-agent framework that leverages GenAI and balances autonomy with the necessary human control. This framework integrates various internal and external systems and is optimized for factors like task orchestration, security, and error mitigation while producing accurate, reliable, and relevant insights by utilizing Retrieval Augmented Generation (RAG). Evaluations of our multi-agent system with the help of practitioners as well as using automated checks demonstrate enhanced accuracy, responsiveness, and effectiveness over non-agentic approaches across complex workflows.

云运维多智能体生成式AI自动化

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