Cloud Infrastructure Management in the Age of AI Agents
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
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| _version_ | 1866908407829626880 |
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| author | Yang, Zhenning Bhatnagar, Archit Qiu, Yiming Miao, Tongyuan Kon, Patrick Tser Jern Xiao, Yunming Huang, Yibo Casado, Martin Chen, Ang |
| author_facet | Yang, Zhenning Bhatnagar, Archit Qiu, Yiming Miao, Tongyuan Kon, Patrick Tser Jern Xiao, Yunming Huang, Yibo Casado, Martin Chen, Ang |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_12270 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cloud Infrastructure Management in the Age of AI Agents Yang, Zhenning Bhatnagar, Archit Qiu, Yiming Miao, Tongyuan Kon, Patrick Tser Jern Xiao, Yunming Huang, Yibo Casado, Martin Chen, Ang Artificial Intelligence Human-Computer Interaction Machine Learning Systems and Control 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. |
| title | Cloud Infrastructure Management in the Age of AI Agents |
| topic | Artificial Intelligence Human-Computer Interaction Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2506.12270 |