# parca-dev/parca

Continuous profiling for analysis of CPU and memory usage, down to the line number and throughout time. Saving infrastructure cost, improving performance, and increasing reliability.

Repository: https://github.com/parca-dev/parca
Canonical: https://ross.abutalabs.com/products/parca
Homepage: https://parca.dev/
Language: TypeScript
License: Apache-2.0
License Family: permissive
Topics: pprof, profiling, continuous-profiling, profiles, prometheus, observability, kubernetes, containers, golang, performance, c, cpp, python, ruby, rust, php, javascript, bpf, ebpf, ebpf-programs
Last push: 2026-08-26T21:40:54+00:00

## Health v2 (maintenance only)
Score: 89/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 71, longevity 100
- inputs: {"age_days": 2836, "days_push": 7, "days_rel": 118, "gap_med": 47, "n_releases_24m": 10}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4951, forks 255 (observed 2026-08-28T04:09:03.716475+00:00)

## What it is
Parca is an open-source continuous profiling server that collects, stores, and queries CPU, memory, and I/O profiles over time, down to the line number. It pairs with an eBPF-based agent that automatically discovers and profiles targets across infrastructure with near-zero instrumentation and low overhead.

## Use cases
- continuously profile CPU and memory usage in production
- find hot code paths to optimize and reduce infrastructure cost
- compare profiling data across deploys, versions, or regions
- investigate memory leaks and CPU spikes during incidents
- auto-discover and profile all workloads in a Kubernetes cluster
- store and query pprof profiles with a label-based query language

## When to choose
- you want always-on, zero-instrumentation profiling across C, C++, Rust, Go, Python, Ruby, PHP, Node.js, and more
- you run Kubernetes or systemd-based infrastructure and want automatic target discovery via eBPF
- you need to store, aggregate, and compare pprof profiles over time with a web UI and flame graphs
- you want a self-hosted, open-source alternative to commercial continuous profilers

## When to avoid
- you need tracing or distributed request-level observability rather than sampling profiles
- you cannot run privileged/root eBPF programs on your Linux hosts
- you need profiling on non-Linux platforms, since the eBPF agent is Linux-only
- you only need ad-hoc, one-off profiling of a single process

## Facets
- artifact type: application
- maturity: active
- function: monitoring, tracing, analytics, search-engine, self-hosted
- domain: monitoring, performance, cloud-computing
- platform: self-hosted, go
- tags: continuous-profiling, pprof, ebpf, observability, flamegraph, prometheus, cpu-profiling, memory-profiling, devops, containers, linux, docker, kubernetes, web-server

## Member repositories
- parca-dev/parca (main) score 89

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:03.716475+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:17:51.913711+00:00, confidence not recorded.
  - readme: https://github.com/parca-dev/parca (fetched 2026-08-28T04:09:03.716475+00:00, sha 3f081e591baf)
  - homepage: https://parca.dev/ (fetched 2026-08-29T08:59:46.419069+00:00, sha 86fe093034bc)
  - site_page: https://www.parca.dev/docs/quickstart (fetched 2026-08-29T08:59:46.428671+00:00, sha 60089c717f76)
  - site_page: https://www.parca.dev/docs/overview (fetched 2026-08-29T08:59:46.431163+00:00, sha 684299f32760)
  - site_page: https://www.parca.dev/docs/binary (fetched 2026-08-29T08:59:46.433579+00:00, sha 3e7261e05e05)
  - site_page: https://www.parca.dev/docs/querying-parca (fetched 2026-08-29T08:59:46.435972+00:00, sha ce8b47b5644e)
  - site_page: https://www.parca.dev/docs/kubernetes (fetched 2026-08-29T08:59:46.437723+00:00, sha e2bb0af726a9)
  - site_page: https://www.parca.dev/docs/faq (fetched 2026-08-29T08:59:46.439599+00:00, sha 8e7fea2e5ef3)
- Data as of 2026-08-30T08:39:29.467469+00:00.