open-telemetry/opentelemetry-ebpf-profiler
open-telemetry/opentelemetry-ebpf-profiler has 3,229 GitHub stars and 446 forks. GitHot measured 0 stars in 24 hours. Last checked 2026-11-08 17:09 UTC. Last push 2026-11-02.
The production-scale datacenter profiler (C/C++, Go, Rust, Python, Java, NodeJS, .NET, PHP, Ruby, Perl, ...)
What you can do
- Implements the Alpha OTel Profiles signal
- Very low CPU and memory overhead (1% CPU and 250MB memory are our upper limits in testing and the agent typically manages to stay way below that)
- Support for native C/C++ executables without the need for DWARF debug information (by leveraging .eh_frame data as described in US11604718B1)
- Support profiling of system libraries without frame pointers and without debug symbols on the host.
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README.md
OriginalOpenTelemetry eBPF Profiler
This repository implements a whole-system, cross-language profiler for Linux via eBPF.
Core features and strengths
- Implements the Alpha OTel Profiles signal
- Very low CPU and memory overhead (1% CPU and 250MB memory are our upper limits in testing and the agent typically manages to stay way below that)
- Support for native C/C++ executables without the need for DWARF debug
information (by leveraging
.eh_framedata as described in US11604718B1) - Support profiling of system libraries without frame pointers and without debug symbols on the host.
- Support for mixed stacktraces between runtimes - stacktraces go from Kernel space through unmodified system libraries all the way into high-level languages.
- Support for native code (C/C++, Rust, Zig, Go, etc. without debug symbols on host)
- Support for a broad set of HLLs, like Hotspot JVM, Python, Ruby, PHP, Node.JS, V8, Perl, Erlang and .NET.
- 100% non-intrusive: there's no need to load agents or libraries into the processes that are being profiled.
- No need for any reconfiguration, instrumentation or restarts of HLL interpreters and VMs: the agent supports unwinding each of the supported languages in the default configuration.
- ARM64 support for all unwinders.
- Support for native
inline frames, which provide insights into compiler optimizations and offer a higher precision of function call chains.
Supported Linux kernel version
The minimum required Linux kernel version has increased with certain commits. Specifically:
- Commit 8047150e was the last to support kernel version 5.4. Subsequent changes may require a minimal Linux kernel version of 5.10 or greater.
- Commit 7ddc23ea was the last to support kernel version 4.19. Subsequent changes may require a minimal Linux kernel version of at least 5.4.
Updating the supported Linux kernel version
The project maintains its minimum supported kernel version in line with the lowest kernel version currently provided by actively maintained major Linux distributions, which include Debian stable, Red Hat Enterprise Linux, Ubuntu LTS, Amazon Linux and SUSE Linux. The minimum requirement may be increased when all such distributions no longer ship a specific kernel version. This approach enables the codebase to utilize newer eBPF features and avoids the need to maintain compatibility shims for obsolete kernels.
It should be noted that certain distributions incorporate eBPF features from newer kernels into their supported versions. When this occurs, the distribution's stated kernel version does not accurately reflect its true eBPF capabilities and will not prevent us from increasing the minimum supported version. On such kernels, the no-kernel-version-check configuration option can be used to bypass the checks and allow the profiler to execute.
Building
The profiler is integrated into the OTel Collector as a receiver. The supported distribution is the recommended way to deploy it.
For development, testing and debugging, a local otelcol-ebpf-profiler binary can be built from this repository. This binary is not supported for production use.
Platform Requirements
The profiler can be built with the provided make targets. Docker is required for containerized builds, and both amd64 and arm64 architectures are supported.
For Linux, the following steps apply:
- Build for your current machine's architecture:
make agent - To cross-compile for a different architecture (e.g. arm64):
make agent TARGET_ARCH=arm64
The resulting binary will be named otelcol-ebpf-profiler in the current directory.
Other OSes
Since the profiler is Linux-only, macOS and Windows users need to set up a Linux VM to build and run it. Use the same make targets above after the Linux environment is configured in the VM.
Building without Docker
You can build without Docker by directly installing the dependencies listed in the Dockerfile. Once dependencies are set up, run:
make
or to build for a specific architecture (e.g. arm64):
make otelcol-ebpf-profiler TARGET_ARCH=arm64
See local.example.yaml for an example configuration.
Running
sudo ./otelcol-ebpf-profiler --feature-gates=+service.profilesSupport --config cmd/otelcol-ebpf-profiler/local.example.yaml
The agent comes with a functional but work-in-progress / evolving implementation of the recently released Alpha OTel Profiles signal.
The agent loads the eBPF program and its maps, starts unwinding and reports captured traces to the backend.
Open Source Backends
As the OTel Profiles signal is still in development, mature production-ready backends have yet to emerge. The following open source projects can be used as backends:
- devfiler — to speed up development and experimentation, Elastic has open-sourced a desktop application that reimplements the backend (collection, data storage, symbolization and UI) portion of the eBPF profiler. Note that devfiler is not a real production backend and should not be used as such. It is solely aimed at testing, experimentation and development.
- Pyroscope — an open source continuous profiling database that natively supports ingesting OTel profiling data.
Contributing
We welcome contributions of all kinds: bug reports, feature requests, documentation improvements and code. Everyone is welcome to open issues and send pull requests.
Before contributing, please read the contributing guidelines. They cover the development prerequisites, how to build and test your changes, the pull request workflow, and how PRs get reviewed and merged.
To understand how this project works and learn more about profiling, check out Profiling internals.
This project is developed by the OpenTelemetry Profiling SIG, which meets regularly. See the OpenTelemetry community repository for the meeting schedule, and join us in the #otel-profiles channel on the CNCF Slack for discussions and questions.
Maintainers
- Felix Geisendörfer, Datadog
- Christos Kalkanis, Elastic
- Timo Teräs
For more information about the maintainer role, see the community repository.
Approvers
- Roger Coll, Grafana Labs
- Florian Lehner, Datadog
- Tim Rühsen
- Nicolas Savoire, Datadog
For more information about the approver role, see the community repository.
Emeritus
- Damien Mathieu, Approver
- Dmitry Filimonov, Maintainer
- Joel Höner, Approver
For more information about the emeritus role, see the community repository.
Become an Approver or a Maintainer
See the community membership document in OpenTelemetry community repo.
Legal
Licensing Information
This project is licensed under the Apache License 2.0 (Apache-2.0). Apache License 2.0
The eBPF source code is licensed under the GPL 2.0 license. GPL 2.0
Licenses of dependencies
To display a summary of the dependencies' licenses:
make legal
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