CloudOpsBench 开源基准发布：推理是 AI 云运维的最大瓶颈
New open-source benchmark reveals reasoning as the biggest bottleneck for AI in cloud operations
密歇根大学 Ang Chen 团队发布开源基准 CloudOpsBench 1.0，用 45 个 AWS 任务评测 AI 智能体的云运维能力，最佳模型 Claude Fable 5.1 仅完成 60%，GPT-6 Astra 为 53%。
Nov 4, 2026
CloudOpsBench is a new open-source benchmark that measures how well AI agents handle typical DevOps tasks in the cloud, from fixing services and removing resources to restricting access rights, rolling out updates, and decommissioning projects. Version 1.0 includes 45 tasks on AWS and was built by experienced DevOps engineers.
Even the best models fail at many of the tasks. Claude Fable 5.1 solved 60 percent, GPT-6 Astra managed 53 percent. According to the team led by Ang Chen at the University of Michigan, the main problem isn't a lack of knowledge but reasoning. About 80 percent of failures happen because agents misjudge the scope of a task, don't check all the relevant services, or stop too early. Roughly 20 percent of errors are wrong actions, some with irreversible consequences for the infrastructure.
All tasks run identically in the real AWS cloud and in an emulator. Extensions for GCP, Azure, and OCI are planned. The project on GitHub is licensed under Apache 2.0, and a detailed failure analysis is also available.
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