<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Llm on CuraDevOps</title><link>https://curadevops.metacog.co.kr/tags/llm/</link><description>Recent content in Llm on CuraDevOps</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 25 Jul 2026 11:58:38 +0000</lastBuildDate><atom:link href="https://curadevops.metacog.co.kr/tags/llm/index.xml" rel="self" type="application/rss+xml"/><item><title>Claude Opus 5 now available in GitHub Copilot</title><link>https://curadevops.metacog.co.kr/insights/2026-07-25-claude-opus-5-is-now-available-in-github-copilot/</link><pubDate>Sat, 25 Jul 2026 11:58:38 +0000</pubDate><guid>https://curadevops.metacog.co.kr/insights/2026-07-25-claude-opus-5-is-now-available-in-github-copilot/</guid><description>&lt;ul>
&lt;li>&lt;strong>Platform/SRE — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>CI/CD — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> A more capable reasoning model is now available in GitHub Copilot; relevant if the org is evaluating AI coding assistant ROI or comparing Copilot seat value against alternatives.&lt;/li>
&lt;/ul></description></item><item><title>Goodput vs throughput: better metric for LLM serving benchmarks</title><link>https://curadevops.metacog.co.kr/insights/2026-07-20-why-goodput-matters-more-than-throughput-for-llm-serving/</link><pubDate>Mon, 20 Jul 2026 13:01:38 +0000</pubDate><guid>https://curadevops.metacog.co.kr/insights/2026-07-20-why-goodput-matters-more-than-throughput-for-llm-serving/</guid><description>&lt;ul>
&lt;li>&lt;strong>Platform/SRE — Learn:&lt;/strong> Reframes how to evaluate LLM inference infrastructure capacity; useful context when sizing or optimizing a self-hosted model-serving stack, but no operational change required today.&lt;/li>
&lt;li>&lt;strong>CI/CD — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Skip&lt;/strong>&lt;/li>
&lt;/ul></description></item><item><title>Self-hosting LLMs on Kubernetes with vLLM (CNCF guide)</title><link>https://curadevops.metacog.co.kr/insights/2026-07-16-running-a-self-hosted-llm-in-kubernetes-with-vllm/</link><pubDate>Thu, 16 Jul 2026 12:15:50 +0000</pubDate><guid>https://curadevops.metacog.co.kr/insights/2026-07-16-running-a-self-hosted-llm-in-kubernetes-with-vllm/</guid><description>&lt;ul>
&lt;li>&lt;strong>Platform/SRE — Learn:&lt;/strong> Useful reference for platform engineers evaluating GPU workload patterns on Kubernetes; no forced migration or deadline, but shapes how you&amp;rsquo;d design node pools and scheduling for LLM inference.&lt;/li>
&lt;li>&lt;strong>CI/CD — Skip&lt;/strong>&lt;/li>
&lt;li>&lt;strong>Leader — Learn:&lt;/strong> Relevant context for build-vs-buy decisions on LLM inference — self-hosting via vLLM vs managed API services — but no concrete strategic decision is forced by this content.&lt;/li>
&lt;/ul></description></item></channel></rss>