# Grafana Pyroscope — Continuous Profiling Backend

> Open-source continuous profiling backend from Grafana Labs that ingests pprof and eBPF profiles, supports label-based queries, and links traces to flamegraphs.

## Install

Save in your project root:

# Grafana Pyroscope — Continuous Profiling for Production

## Quick Use
```bash
# Run the single-binary all-in-one
docker run -d --name pyroscope -p 4040:4040 
  grafana/pyroscope:latest

# Profile a Go service (push mode)
go get github.com/grafana/pyroscope-go
# in main.go:
#   pyroscope.Start(pyroscope.Config{
#     ApplicationName: "my.svc",
#     ServerAddress:   "http://pyroscope:4040",
#   })

# Or scrape Go pprof endpoints (pull mode) via pyroscope.yaml
```

## Introduction
Pyroscope is a continuous profiling backend that records CPU, memory, goroutine, and lock profiles from production services and lets you slice them by label like a time-series. After joining the Grafana Labs family, it was merged with Phlare into a single Grafana-integrated backend that supports both pull (pprof-scrape) and push (agent SDK) ingestion.

## What Pyroscope Does
- Collects pprof-compatible profiles from Go, Java, Python, Ruby, .NET, Node.js, Rust, and eBPF.
- Provides a flamegraph-first UI with "diff" mode for comparing time ranges or deployments.
- Exposes profiles under labels (service, region, deployment) like Prometheus time series.
- Integrates natively with Grafana for dashboards combining metrics, logs, traces, and profiles.
- Supports "span profiles" — traces linked to the specific flamegraph frames that ran in them.

## Architecture Overview
Pyroscope v1 is a horizontally-scalable backend derived from Grafana Phlare. Distributors accept push ingestion; Ingesters build time-partitioned profile blocks in object storage (S3/GCS/Azure); Queriers fan out reads across block metadata, with Compactors merging blocks for long-term retention. A single-binary mode collapses all roles for dev and small clusters. On the agent side, Grafana Alloy (or the standalone Pyroscope agent) handles scraping pprof endpoints and running eBPF profilers node-wide.

## Self-Hosting & Configuration
- Helm chart: `helm install pyroscope grafana/pyroscope` (single-binary by default).
- Configure storage in `pyroscope.yaml` — set `storage.backend=s3` and an S3 bucket for prod.
- Push SDKs auto-profile at 100 Hz by default; tune `SampleRate` for heavy workloads.
- eBPF profiler DaemonSet runs CPU profiles across a node for uninstrumented languages.
- Grafana plugin ships built-in — add Pyroscope as a data source to get flamegraphs.

## Key Features
- pprof-compatible format — dump, diff, and inspect with standard tooling.
- Label-based profile queries with PromQL-like selectors.
- eBPF whole-node profiling without touching application code.
- Trace-to-profile linking: click a trace span to see the exact flamegraph for that span.
- Scales from single binary to multi-service HA on object storage.

## Comparison with Similar Tools
- **Parca** — open-source eBPF continuous profiling; Pyroscope is broader in language support.
- **Datadog Continuous Profiler** — SaaS, similar capabilities; Pyroscope is self-hostable.
- **Polar Signals Cloud** — managed Parca; same idea, hosted.
- **elastic/otel-profiling-agent** — eBPF profiler feeding Elastic; Pyroscope supports pprof and OTel profiles.
- **Classic pprof** — CLI only; Pyroscope makes it a continuous time-series system.

## FAQ
**Q:** Do I have to instrument code to use it?
A: Not for CPU: the eBPF profiler covers Go, Rust, C/C++, Python, Java, .NET without code changes.

**Q:** How much storage does it use?
A: Profiles are small and compress well; typical services cost far less than their metrics stream.

**Q:** Can I diff two deployments?
A: Yes, the UI supports flamegraph diff across arbitrary label sets.

**Q:** Is it part of Grafana Cloud?
A: Yes; the open-source code here is the same engine that powers the Grafana Cloud Profiles product.

## Sources
- https://github.com/grafana/pyroscope
- https://grafana.com/docs/pyroscope/latest/


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Source: https://tokrepo.com/en/workflows/138e4edf-38d7-11f1-9bc6-00163e2b0d79
Author: AI Open Source