/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.

Primary LanguageTypeScriptApache License 2.0Apache-2.0

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Parca: Continuous profiling for analysis of CPU, memory usage over time, and down to the line number.

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

Screenshot of Parca

Features

  • eBPF Profiler: A single profiler, using eBPF, automatically discovering targets from Kubernetes or systemd across the entire infrastructure with very low overhead. Supports C, C++, Rust, Go, and more!

  • Open Standards: Both producing pprof formatted profiles with the eBPF based profiler, and ingesting any pprof formatted profiles allowing for wide language adoption and interoperability with existing tooling.

  • Optimized Storage & Querying: Efficiently storing profiling data while retaining raw data and allowing slicing and dicing of data through a label-based search. Aggregate profiling data infrastructure wide, view single profiles in time or compare on any dimension.

Why?

  • Save Money: Many organizations have 20-30% of resources wasted with easily optimized code paths. The Parca Agent aims to lower the entry bar by requiring 0 instrumentation for the whole infrastructure. Deploy in your infrastructure and get started!
  • Improve Performance: Using profiling data collected over time, Parca can with confidence and statistical significance determine hot paths to optimize. Additionally it can show differences between any label dimension, such as deploys, versions, and regions.
  • Understand Incidents: Profiling data provides unique insight and depth into what a process executed over time. Memory leaks, but also momentary spikes in CPU or I/O causing unexpected behavior, is traditionally difficult to troubleshoot are a breeze with continuous profiling.

Feedback & Support

If you have any feedback, please open a discussion in the GitHub Discussions of this project. We would love to learn what you think!

Installation & Documentation

Check Parca's website for updated and in-depth installation guides and documentation!

parca.dev

Development

You need to have Go, Node and Yarn installed.

Clone the project

git clone https://github.com/parca-dev/parca.git

Go to the project directory

cd parca

Build the UI and compile the Go binaries

make build

Running the compiled Parca binary

The binary was compiled to bin/parca .

./bin/parca

Now Parca is running locally and its web UI is available on http://localhost:7070/.

By default Parca is scraping it's own pprof endpoints and you should see profiles show up over time. The scrape configuration can be changed in the parca.yaml in the root of the repository.

Configuration

Flags:

Usage: parca

Flags:
  -h, --help                    Show context-sensitive help.
      --config-path="parca.yaml"
                                Path to config file.
      --mode="all"              Scraper only runs a scraper that sends to a
                                remote gRPC endpoint. All runs all components.
      --http-address=":7070"    Address to bind HTTP server to.
      --port=""                 (DEPRECATED) Use http-address instead.
      --log-level="info"        Log level.
      --log-format="logfmt"     Configure if structured logging as JSON or as
                                logfmt
      --cors-allowed-origins=CORS-ALLOWED-ORIGINS,...
                                Allowed CORS origins.
      --otlp-address=STRING     OpenTelemetry collector address to send traces
                                to.
      --version                 Show application version.
      --path-prefix=""          Path prefix for the UI
      --mutex-profile-fraction=0
                                Fraction of mutex profile samples to collect.
      --block-profile-rate=0    Sample rate for block profile.
      --enable-persistence      Turn on persistent storage for the metastore and
                                profile storage.
      --storage-granule-size=26265625
                                Granule size in bytes for storage.
      --storage-active-memory=536870912
                                Amount of memory to use for active storage.
                                Defaults to 512MB.
      --storage-path="data"     Path to storage directory.
      --storage-enable-wal      Enables write ahead log for profile storage.
      --storage-row-group-size=8192
                                Number of rows in each row group during
                                compaction and persistence. Setting to <= 0
                                results in a single row group per file.
      --symbolizer-demangle-mode="simple"
                                Mode to demangle C++ symbols. Default mode
                                is simplified: no parameters, no templates,
                                no return type
      --symbolizer-number-of-tries=3
                                Number of tries to attempt to symbolize an
                                unsybolized location
      --debuginfo-cache-dir="/tmp"
                                Path to directory where debuginfo is cached.
      --debuginfo-upload-max-size=1000000000
                                Maximum size of debuginfo upload in bytes.
      --debuginfo-upload-max-duration=15m
                                Maximum duration of debuginfo upload.
      --debuginfo-uploads-signed-url
                                Whether to use signed URLs for debuginfo
                                uploads.
      --debuginfod-upstream-servers=https://debuginfod.elfutils.org,...
                                Upstream debuginfod servers. Defaults to
                                https://debuginfod.elfutils.org. It is an
                                ordered list of servers to try. Learn more at
                                https://sourceware.org/elfutils/Debuginfod.html
      --debuginfod-http-request-timeout=5m
                                Timeout duration for HTTP request to upstream
                                debuginfod server. Defaults to 5m
      --metastore="badger"      Which metastore implementation to use
      --profile-share-server="api.pprof.me:443"
                                gRPC address to send share profile requests to.
      --store-address=STRING    gRPC address to send profiles and symbols to.
      --bearer-token=STRING     Bearer token to authenticate with store.
      --bearer-token-file=STRING
                                File to read bearer token from to authenticate
                                with store.
      --insecure                Send gRPC requests via plaintext instead of TLS.
      --insecure-skip-verify    Skip TLS certificate verification.
      --external-label=KEY=VALUE;...
                                Label(s) to attach to all profiles in
                                scraper-only mode.
      --experimental-arrow      EXPERIMENTAL: Enables Arrow ingestion, this will
                                reduce CPU usage but will increase memory usage.

Credits

Parca was originally developed by Polar Signals. Read the announcement blog post: https://www.polarsignals.com/blog/posts/2021/10/08/introducing-parca-we-got-funded/

Contributing

Check out our Contributing Guide to get started! It explains how compile Parca, run it with Tilt as container in Kubernetes and send a Pull Request.

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Frederic Branczyk
Frederic Branczyk

πŸ’» πŸ“– πŸš‡
Thor
Thor

πŸ’» πŸ“– πŸš‡
Matthias Loibl
Matthias Loibl

πŸ’» πŸ“– πŸš‡
Kemal Akkoyun
Kemal Akkoyun

πŸ’» πŸ“–
Sumera Priyadarsini
Sumera Priyadarsini

πŸ’» πŸ“–
JΓ©ssica Lins
JΓ©ssica Lins

πŸ“–
Holger Freyther
Holger Freyther

πŸ’»
Sergiusz Urbaniak
Sergiusz Urbaniak

πŸš‡
PaweΕ‚ Krupa
PaweΕ‚ Krupa

πŸš‡
Ben Ye
Ben Ye

πŸ’» πŸš‡
Felix
Felix

πŸ’» πŸ“– πŸš‡
Christian Bargmann
Christian Bargmann

πŸ’»
Yomi Eluwande
Yomi Eluwande

πŸ’» πŸ“–
Manoj Vivek
Manoj Vivek

πŸ’» πŸ“–
Monica Wojciechowska
Monica Wojciechowska

πŸ’» πŸ“–
Manuel RΓΌger
Manuel RΓΌger

πŸš‡
Avinash Upadhyaya K R
Avinash Upadhyaya K R

πŸ’»
Ikko Ashimine
Ikko Ashimine

πŸ’»
Maxime Brunet
Maxime Brunet

πŸ’» πŸš‡
rohit
rohit

πŸ’»
Ujjwal Goyal
Ujjwal Goyal

πŸ“–
Javier Honduvilla Coto
Javier Honduvilla Coto

πŸ’»
Marsel Mavletkulov
Marsel Mavletkulov

πŸ’»
Kautilya Tripathi
Kautilya Tripathi

πŸ’»
Jon Seager
Jon Seager

πŸ’»
Philip Gough
Philip Gough

πŸ’»
Boran Seref
Boran Seref

πŸ’»
Wen Long
Wen Long

πŸ’»
cui fliter
cui fliter

πŸ“–
Alfonso Subiotto MarquΓ©s
Alfonso Subiotto MarquΓ©s

πŸ’»
TomHellier
TomHellier

πŸ’»
Stefan VanBuren
Stefan VanBuren

πŸ’»
Carlos Tadeu Panato Junior
Carlos Tadeu Panato Junior

πŸš‡
Daniel (Shijun) Qian
Daniel (Shijun) Qian

πŸ’»
Alex Vest
Alex Vest

πŸ“–
Shubham Palriwala
Shubham Palriwala

πŸ’»
Fabian Reinartz
Fabian Reinartz

πŸ’»

This project follows the all-contributors specification. Contributions of any kind welcome!