用大模型智能体自动管理云基础设施，减少人工运维负担。
Cloud Infrastructure Management in the Age of AI Agents
- 构建基于大模型的智能体，通过SDK、CLI、IaC和网页端操作云资源。
- 实验发现不同接口在任务完成率上差异显著，CLI表现最优。
- 适合关注AI+运维、自动化工具链研发的研究者与工程师。
云基础设施是现代IT产业的核心。然而，有效管理这些设施需要开发运维团队投入大量人力。本文主张利用大语言模型（LLM）驱动的AI智能体来自动化云基础设施管理任务。在一项初步研究中，我们评估了AI智能体通过软件开发工具包（SDK）、命令行界面（CLI）、基础设施即代码（IaC）平台以及网页门户等不同接口执行管理任务的可行性。研究揭示了各类接口在任务执行效率上的差异，并识别出关键研究挑战及潜在解决方案。
原文摘要 · Abstract (English)
Cloud infrastructure is the cornerstone of the modern IT industry. However, managing this infrastructure effectively requires considerable manual effort from the DevOps engineering team. We make a case for developing AI agents powered by large language models (LLMs) to automate cloud infrastructure management tasks. In a preliminary study, we investigate the potential for AI agents to use different cloud/user interfaces such as software development kits (SDK), command line interfaces (CLI), Infrastructure-as-Code (IaC) platforms, and web portals. We report takeaways on their effectiveness on different management tasks, and identify research challenges and potential solutions.
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