<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Profiling on Pi Stack</title><link>https://www.pistack.xyz/tags/profiling/</link><description>Recent content in Profiling on Pi Stack</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Sat, 18 Apr 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://www.pistack.xyz/tags/profiling/index.xml" rel="self" type="application/rss+xml"/><item><title>Grafana Pyroscope vs Parca vs Profefe: Best Self-Hosted Continuous Profiling Platforms 2026</title><link>https://www.pistack.xyz/posts/2026-04-18-grafana-pyroscope-vs-parca-vs-profefe-self-hosted-continuous-profiling-guide-2026/</link><pubDate>Sat, 18 Apr 2026 00:00:00 +0000</pubDate><guid>https://www.pistack.xyz/posts/2026-04-18-grafana-pyroscope-vs-parca-vs-profefe-self-hosted-continuous-profiling-guide-2026/</guid><description>&lt;p>Continuous profiling captures performance data from your running applications at all times — CPU usage, memory allocations, blocking profiles, and goroutine contention — without the overhead of manual sampling sessions. Unlike traditional profiling where you attach a profiler for a few minutes and hope to catch the problem, continuous profiling keeps a running history you can query retroactively when incidents occur.&lt;/p></description></item></channel></rss>