<?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 Techetio</title><link>https://techetio.com/tag/prometheus/</link><description>Recent content in Prometheus on Techetio</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sun, 19 Oct 2025 17:44:39 +0000</lastBuildDate><atom:link href="https://techetio.com/tag/prometheus/index.xml" rel="self" type="application/rss+xml"/><item><title>Doing Deadman Checks With Prometheus Metrics in MetricsQL</title><link>https://techetio.com/2025/10/19/doing-deadman-checks-with-prometheus-metrics-in-metricsql/</link><pubDate>Sun, 19 Oct 2025 17:44:39 +0000</pubDate><guid>https://techetio.com/2025/10/19/doing-deadman-checks-with-prometheus-metrics-in-metricsql/</guid><description>&lt;p&gt;The lack of functionality to do deadman checks is one of my biggest gripes with PromQL. Fortunately, MetricsQL (a superset of PromQL) has added this functionality, and it&amp;rsquo;s very easy to use. If you&amp;rsquo;re not familiar with MetricsQL, it&amp;rsquo;s the built in query language in VictoriaMetrics, a horizontally scalable time series database. VictoriaMetrics is my go to database for storing Prometheus metrics because of how performant and easy to use it is compared to alternatives like Mimir or Thanos.&lt;/p&gt;</description></item></channel></rss>