{"id":757,"date":"2024-11-19T10:00:00","date_gmt":"2024-11-19T10:00:00","guid":{"rendered":"https:\/\/jacar.es\/ebpf-profiling-continuo\/"},"modified":"2024-11-19T10:00:00","modified_gmt":"2024-11-19T10:00:00","slug":"ebpf-profiling-continuo","status":"publish","type":"post","link":"https:\/\/jacar.es\/en\/ebpf-profiling-continuo\/","title":{"rendered":"eBPF for Continuous Profiling: Parca and Beyla"},"content":{"rendered":"<p><strong>eBPF-based continuous profiling<\/strong> transforms debugging from \u201cad-hoc pprof when it fails\u201d to \u201calways-on profile.\u201d 2024 modern stack: <strong><a href=\"https:\/\/www.parca.dev\/\">Parca<\/a><\/strong>, <strong><a href=\"https:\/\/grafana.com\/oss\/beyla\/\">Grafana Beyla<\/a><\/strong>, <strong><a href=\"https:\/\/pyroscope.io\/\">Pyroscope<\/a><\/strong> (now Grafana). This article covers complementary roles + integration patterns.<\/p>\n<h2 id=\"the-stack\">The Stack<\/h2>\n<p>Three complementary tools:<\/p>\n<ul>\n<li><strong>Parca<\/strong>: 24\/7 CPU profiling via eBPF.<\/li>\n<li><strong>Beyla<\/strong>: HTTP auto-instrumentation + metrics + traces.<\/li>\n<li><strong>Pyroscope<\/strong>: language-specific deep profiling.<\/li>\n<\/ul>\n<p>Combined: cluster-wide coverage + targeted depth.<\/p>\n<h2 id=\"parca-what-it-covers\">Parca: What It Covers<\/h2>\n<p>Installs DaemonSet, eBPF agent per node:<\/p>\n<ul>\n<li><strong>Cluster-wide CPU flame graphs<\/strong>.<\/li>\n<li><strong>Compiled languages<\/strong>: Go, Rust, C++ (deep stack unwinding).<\/li>\n<li><strong>Interpreted<\/strong>: Python, Node (interpreter frames).<\/li>\n<li><strong>Prometheus-compatible<\/strong>: metrics + labels.<\/li>\n<li><strong>Minimal overhead<\/strong>: 0.5-1% CPU.<\/li>\n<\/ul>\n<h2 id=\"beyla-auto-instrumentation\">Beyla: Auto-Instrumentation<\/h2>\n<p>Covers:<\/p>\n<ul>\n<li><strong>HTTP\/gRPC traces<\/strong> without SDK changes.<\/li>\n<li><strong>RED metrics<\/strong> (rate, errors, duration).<\/li>\n<li><strong>Automatic service graphs<\/strong>.<\/li>\n<li><strong>Standard OTel output<\/strong>.<\/li>\n<\/ul>\n<p>Not profiling per se \u2014 instrumentation without code changes.<\/p>\n<h2 id=\"pyroscope\">Pyroscope<\/h2>\n<p>Originally independent, now part of Grafana:<\/p>\n<ul>\n<li><strong>Language agents<\/strong>: native libraries, deeper info.<\/li>\n<li><strong>Compiled + interpreted<\/strong>: richer data.<\/li>\n<li><strong>Storage\/querying backend<\/strong>: can ingest from Parca.<\/li>\n<\/ul>\n<p>Use case: deeper language-specific profiling for specific critical apps.<\/p>\n<h2 id=\"install\">Install<\/h2>\n<h3 id=\"parca\">Parca<\/h3>\n<div class=\"sourceCode\" id=\"cb1\">\n<pre class=\"sourceCode bash\"><code class=\"sourceCode bash\"><span id=\"cb1-1\"><a href=\"#cb1-1\" aria-hidden=\"true\" tabindex=\"-1\"><\/a><span class=\"ex\">helm<\/span> install parca parca\/parca<\/span>\n<span id=\"cb1-2\"><a href=\"#cb1-2\" aria-hidden=\"true\" tabindex=\"-1\"><\/a><span class=\"ex\">helm<\/span> install parca-agent parca\/parca-agent <span class=\"at\">--namespace<\/span> monitoring<\/span><\/code><\/pre>\n<\/div>\n<p>Per-node agent, centralised Parca server. Auto-discovers processes.<\/p>\n<h3 id=\"beyla\">Beyla<\/h3>\n<div class=\"sourceCode\" id=\"cb2\">\n<pre class=\"sourceCode bash\"><code class=\"sourceCode bash\"><span id=\"cb2-1\"><a href=\"#cb2-1\" aria-hidden=\"true\" tabindex=\"-1\"><\/a><span class=\"ex\">helm<\/span> install beyla grafana\/beyla <span class=\"dt\">\\<\/span><\/span>\n<span id=\"cb2-2\"><a href=\"#cb2-2\" aria-hidden=\"true\" tabindex=\"-1\"><\/a>  <span class=\"at\">--set<\/span> env.BEYLA_AUTO_INSTRUMENT_TARGET=my-app<\/span><\/code><\/pre>\n<\/div>\n<h3 id=\"pyroscope-1\">Pyroscope<\/h3>\n<div class=\"sourceCode\" id=\"cb3\">\n<pre class=\"sourceCode bash\"><code class=\"sourceCode bash\"><span id=\"cb3-1\"><a href=\"#cb3-1\" aria-hidden=\"true\" tabindex=\"-1\"><\/a><span class=\"ex\">helm<\/span> install pyroscope grafana\/pyroscope<\/span><\/code><\/pre>\n<\/div>\n<h2 id=\"grafana-integration\">Grafana Integration<\/h2>\n<p>Unified stack:<\/p>\n<ul>\n<li><strong>Grafana Tempo<\/strong>: traces.<\/li>\n<li><strong>Grafana Mimir<\/strong>: metrics.<\/li>\n<li><strong>Grafana Loki<\/strong>: logs.<\/li>\n<li><strong>Grafana Pyroscope<\/strong>: profiles (+ Parca ingestion).<\/li>\n<li><strong>Grafana<\/strong>: single dashboard.<\/li>\n<\/ul>\n<p>Click trace \u2192 see profile of that period. Strong correlation.<\/p>\n<h2 id=\"real-overhead\">Real Overhead<\/h2>\n<p>Measured in production:<\/p>\n<ul>\n<li><strong>Parca<\/strong>: ~0.5-1% CPU per node.<\/li>\n<li><strong>Beyla<\/strong>: ~1-2% CPU, 50MB memory.<\/li>\n<li><strong>Pyroscope language agent<\/strong>: 1-5% depending.<\/li>\n<\/ul>\n<p>Combined &lt;5% \u2014 acceptable.<\/p>\n<h2 id=\"use-cases\">Use Cases<\/h2>\n<h3 id=\"detect-regressions\">Detect Regressions<\/h3>\n<p>Deploy new version \u2192 Parca shows increased CPU in specific function \u2192 rollback before user impact.<\/p>\n<h3 id=\"optimise-hotspots\">Optimise Hotspots<\/h3>\n<p>Weekly flame graphs review \u2192 identify top-10 CPU consumers \u2192 optimise.<\/p>\n<h3 id=\"compare-periods\">Compare Periods<\/h3>\n<p>\u201cWhy is latency up this week?\u201d \u2192 compare profiles last week vs this week.<\/p>\n<h3 id=\"root-cause-incidents\">Root Cause Incidents<\/h3>\n<p>Post-mortem: profile during incident vs baseline highlights specific function.<\/p>\n<h2 id=\"flame-graph-interpretation\">Flame Graph Interpretation<\/h2>\n<p>Basics:<\/p>\n<ul>\n<li><strong>Width = CPU time<\/strong>.<\/li>\n<li><strong>Stack from bottom up<\/strong>.<\/li>\n<li><strong>Hot paths = wide top-level boxes<\/strong>.<\/li>\n<\/ul>\n<p>Skill \u2014 learn with Brendan Gregg tutorials.<\/p>\n<h2 id=\"language-specifics\">Language Specifics<\/h2>\n<h3 id=\"go\">Go<\/h3>\n<p>Parca excellent: DWARF info, full stacks. Preferred.<\/p>\n<h3 id=\"rust\">Rust<\/h3>\n<p>Similar to Go \u2014 compiled, rich stacks.<\/p>\n<h3 id=\"pythonnode\">Python\/Node<\/h3>\n<p>Interpreter frames visible. For Python-level detail, Pyroscope language agent better.<\/p>\n<h3 id=\"java\">Java<\/h3>\n<p>Complex JVM. Specialised Pyroscope Java agent.<\/p>\n<h3 id=\"cc\">C\/C++<\/h3>\n<p>Native \u2014 Parca perfect.<\/p>\n<h2 id=\"cost\">Cost<\/h2>\n<ul>\n<li><strong>Storage<\/strong>: compressed profile samples ~1GB\/day for 50-node cluster.<\/li>\n<li><strong>S3 or similar<\/strong> for long-term.<\/li>\n<li><strong>Retention<\/strong>: typically 15-30 days.<\/li>\n<\/ul>\n<p>Manageable.<\/p>\n<h2 id=\"alternatives\">Alternatives<\/h2>\n<ul>\n<li><strong>Datadog Continuous Profiler<\/strong>: commercial, mature, multi-language.<\/li>\n<li><strong>New Relic<\/strong>: similar.<\/li>\n<li><strong>Elastic Profiling<\/strong>: newer.<\/li>\n<li><strong>Cloudflare AMP<\/strong>: specific context.<\/li>\n<\/ul>\n<p>Open-source Parca\/Beyla\/Pyroscope stack has comparable features + free.<\/p>\n<h2 id=\"security\">Security<\/h2>\n<p>eBPF-based tools require:<\/p>\n<ul>\n<li><strong>Privileged container<\/strong>.<\/li>\n<li><strong>HostPID \/ HostNetwork<\/strong>.<\/li>\n<li><strong>Sufficiently recent kernel<\/strong> (5.10+).<\/li>\n<\/ul>\n<p>Attack surface consideration. Restrict RBAC.<\/p>\n<h2 id=\"for-new-adopters\">For New Adopters<\/h2>\n<p>Start path:<\/p>\n<ol type=\"1\">\n<li><strong>Install Parca in staging<\/strong>.<\/li>\n<li><strong>Review flame graphs<\/strong> for weeks.<\/li>\n<li><strong>Skill build<\/strong> interpreting profiles.<\/li>\n<li><strong>Deploy production<\/strong> carefully.<\/li>\n<li><strong>Correlate with traces\/logs<\/strong> setup.<\/li>\n<\/ol>\n<p>Skill + value accumulate.<\/p>\n<h2 id=\"when-profiling-not-useful\">When Profiling Not Useful<\/h2>\n<ul>\n<li><strong>No performance issues<\/strong> \u2014 wasted effort.<\/li>\n<li><strong>Simple workloads<\/strong> \u2014 htop suffices.<\/li>\n<li><strong>No expertise<\/strong> interpreting \u2014 data without action.<\/li>\n<\/ul>\n<p>Most production systems benefit; some don\u2019t.<\/p>\n<h2 id=\"conclusion\">Conclusion<\/h2>\n<p>Continuous profiling via eBPF is significant improvement over ad-hoc pprof. Parca + Beyla + Pyroscope stack covers spectrum without big commercial cost. For performance-sensitive ops, invest. Flame-graph interpretation skill pays. Grafana stack integration seamless. Modern production observability increasingly includes profiling as fourth pillar (after metrics\/logs\/traces). Now is good time to adopt.<\/p>\n<p>Follow us on jacar.es for more on eBPF, profiling, and observability stacks.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>24\/7 whole-cluster profiling without instrumenting apps. Parca + Beyla modern stack for performance observability.<\/p>\n","protected":false},"author":1,"featured_media":758,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19],"tags":[591,59,519,516,696,697],"class_list":["post-757","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tecnologia","tag-beyla","tag-ebpf","tag-observability","tag-parca","tag-profiling","tag-pyroscope"],"translation":{"provider":"WPGlobus","version":"3.0.2","language":"en","enabled_languages":["es","en"],"languages":{"es":{"title":true,"content":true,"excerpt":true},"en":{"title":true,"content":true,"excerpt":true}}},"gutentor_comment":0,"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>eBPF for Continuous Profiling: Parca and Beyla - Jacar<\/title>\n<meta name=\"description\" content=\"eBPF continuous profiling stack: Parca + Beyla + Pyroscope. 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