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面向DevOps的生成式AI课程涵盖GPU基础设施和LLM服务

作者 PulseAugur 编辑部 · [4 个来源] ·

一系列帖子详细介绍了“面向DevOps的100天生成式AI”课程，重点关注运行大型语言模型的基础设施和运营方面。该课程涵盖了诸如Kubernetes中的GPU利用率、vLLM等高效LLM服务框架以及LLM的GPU内存需求计算等主题。它旨在为DevOps、SRE和平台工程师提供将AI集成到其工具包中的技能，超越基础的提示工程，转向构建和管理由AI驱动的解决方案。 AI

影响 为工程师提供管理AI基础设施的实用技能，从基础使用转向运营部署。

排序理由 该集群描述了一门课程及其课程内容，而非新产品或技术发布。

在 dev.to — LLM tag 阅读 →

AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →

面向DevOps的生成式AI课程涵盖GPU基础设施和LLM服务

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该集群描述了一门课程及其课程内容，而非新产品或技术发布。
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4 independent sources
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product, infra
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56 days old
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报道来源 [4]

  1. dev.to — LLM tag TIER_1 English(EN) · Prashant Lakhera ·

    🚀 第18天：DevOps的100天GenAI：Kubernetes与GPU

    <p>How does Kubernetes actually run an LLM on a GPU?</p> <p>That was the focus of Day 18.</p> <p>Kubernetes understands CPU and memory by default, but GPUs require additional components. We walked through the complete journey:</p> <p>🔹 NFD (Node Feature Discovery) — Discovers GPU…

  2. dev.to — LLM tag TIER_1 English(EN) · Prashant Lakhera ·

    🚀 100天GenAI赋能DevOps — 理解vLLM 第17天

    <p>Running an LLM on your laptop is one thing.</p> <p>Serving that LLM efficiently to hundreds or thousands of users is a completely different challenge.</p> <p>In Day 17 of 100 Days of GenAI for DevOps, we explore vLLM, an open-source LLM serving framework designed for fast and …

  3. dev.to — LLM tag TIER_1 English(EN) · Prashant Lakhera ·

    🚀 第二天完成 – 面向 DevOps 工程师的 GenAI！

    <p>Today, we wrapped up Day 2 of our August GenAI for DevOps Engineers batch.</p> <p>Today’s discussion focused on two important topics:</p> <p>🔹 GPU for DevOps Engineers<br /> We explored why GPUs have become such an important part of modern AI infrastructure and what DevOps, SR…

  4. dev.to — LLM tag TIER_1 English(EN) · Prashant Lakhera ·

    🚀 仅剩 12 小时报名：面向 DevOps 工程师的 GenAI！🚀

    <p>🚀 Only 12 Hours Left to Enroll: GenAI for DevOps Engineers!🚀 </p> <p>DevOps is evolving again.</p> <p>📌 We moved from physical servers → cloud.</p> <p>📌 From manual deployments → CI/CD.</p> <p>📌 From traditional operations → DevOps, SRE, and Platform Engineering.</p> <p>📌 And …

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