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NVIDIA AI 工厂全栈可观测性选型指南
原标题：How to Choose Full-Stack Observability for NVIDIA AI Factories
AI 摘要
NVIDIA 技术博客发布了一篇关于 AI 工厂全栈可观测性选型的指南，针对 AI 基础设施多层架构中故障定位难的问题，提出了一个基于 NVIDIA DGX 部署的决策框架。文章通过分布式训练中 InfiniBand 链路静默故障的案例，说明了全栈可观测性的重要性，并给出了组件到遥测工具的映射表，帮助运维团队选择最小工具集并构建分诊仪表板。
以上摘要由 AI 生成，可能存在误差。事实请以原文为准。
正文节选
AI infrastructure spans multiple layers, from compute and networking to storage, orchestration, and applications. When performance degrades, identifying the source can be difficult because a symptom observed at one layer may originate elsewhere in the stack. A full-stack observability strategy connects telemetry across these layers, helping infrastructure and operations teams detect problems, isolate their causes, and maintain reliable AI workloads. This post presents a practical observability f
发布时间：2026-08-13 00:13
抓取时间：2026-08-13 01:02
来源机构：NVIDIA