<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>AI基础设施 on 黄文卓 | DevOps Engineer</title><link>https://socake.github.io/tags/ai%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/</link><description>Recent content in AI基础设施 on 黄文卓 | DevOps Engineer</description><generator>Hugo -- gohugo.io</generator><language>zh-CN</language><managingEditor>17691281867@163.com (Wenzhuo Huang)</managingEditor><webMaster>17691281867@163.com (Wenzhuo Huang)</webMaster><copyright>© 2026 Wenzhuo Huang</copyright><lastBuildDate>Wed, 05 Nov 2025 14:00:00 +0800</lastBuildDate><atom:link href="https://socake.github.io/tags/ai%E5%9F%BA%E7%A1%80%E8%AE%BE%E6%96%BD/index.xml" rel="self" type="application/rss+xml"/><item><title>Kubernetes GPU 调度实战：AI 训练与推理基础设施</title><link>https://socake.github.io/posts/kubernetes-gpu-scheduling/</link><pubDate>Wed, 05 Nov 2025 14:00:00 +0800</pubDate><author>17691281867@163.com (Wenzhuo Huang)</author><guid>https://socake.github.io/posts/kubernetes-gpu-scheduling/</guid><description>GPU 是 AI 基础设施的核心资源，如何在 Kubernetes 上高效调度和管理 GPU 直接影响训练效率和推理成本。本文从底层驱动安装到上层调度策略，完整覆盖 K8s GPU 基础设施的搭建、监控和优化实践。</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://socake.github.io/posts/kubernetes-gpu-scheduling/featured.jpg"/></item></channel></rss>