<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Guides on Modelplane Docs</title><link>https://v0-1.docs.modelplane.ai/guides/</link><description>Recent content in Guides on Modelplane Docs</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Mon, 01 Jan 0001 00:00:00 +0000</lastBuildDate><atom:link href="https://v0-1.docs.modelplane.ai/guides/index.xml" rel="self" type="application/rss+xml"/><item><title>Collecting engine metrics</title><link>https://v0-1.docs.modelplane.ai/guides/collecting-engine-metrics/</link><pubDate/><guid>https://v0-1.docs.modelplane.ai/guides/collecting-engine-metrics/</guid><description>&lt;!-- vale write-good.Passive = NO --&gt;
&lt;p&gt;Scraping an inference engine&amp;rsquo;s Prometheus metrics, shown on the smallest serving
shape: a 0.5B Qwen chat model on one NVIDIA L4. vLLM publishes metrics at
&lt;code&gt;/metrics&lt;/code&gt; on its serving port with no extra flag, and Modelplane runs a
Prometheus on every workload cluster with &lt;code&gt;PodMonitor&lt;/code&gt; discovery open across
namespaces, so scraping the engine is a &lt;code&gt;PodMonitor&lt;/code&gt; plus a &lt;code&gt;port-forward&lt;/code&gt;. The
model is only the subject; the same wiring fits any engine, with the SGLang,
leader/worker, and prefill/decode differences noted at the end.&lt;/p&gt;</description></item></channel></rss>