<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Prometheus on vsz@ | Kubernetes, AI, tech stuff</title><link>https://victorszalvay.com/tags/prometheus/</link><description>Recent content in Prometheus on vsz@ | Kubernetes, AI, tech stuff</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>Victor Szalvay — All rights reserved</copyright><lastBuildDate>Sat, 26 Sep 2026 09:00:00 -0700</lastBuildDate><atom:link href="https://victorszalvay.com/tags/prometheus/index.xml" rel="self" type="application/rss+xml"/><item><title>How often did your top rule actually win? A ComputeClass fulfillment dashboard</title><link>https://victorszalvay.com/computeclass-priority-fulfillment/</link><pubDate>Sat, 26 Sep 2026 09:00:00 -0700</pubDate><guid>https://victorszalvay.com/computeclass-priority-fulfillment/</guid><description>&lt;p&gt;&lt;em&gt;A ComputeClass is a ranked list of capacity preferences: try this shape first, fall back
to that one. GKE numbers those rules from zero, so your top choice is &amp;ldquo;rule 0&amp;rdquo; — and the
&lt;code&gt;ccc_priority_index&lt;/code&gt; node annotation records which rule actually won each node. Aggregate
it over time and you can finally answer the question the per-node view can&amp;rsquo;t: how much of
the capacity you got came from your first choice? Here&amp;rsquo;s a working exporter, a Cloud
Monitoring dashboard, and an argument about what &amp;ldquo;volume&amp;rdquo; should mean on that chart.&lt;/em&gt;&lt;/p&gt;</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://victorszalvay.com/computeclass-priority-fulfillment/cover.png"/></item></channel></rss>