parca-agent
austin-tui
parca-agent | austin-tui | |
---|---|---|
10 | 4 | |
484 | 617 | |
5.0% | - | |
9.9 | 2.3 | |
1 day ago | 12 months ago | |
Go | Python | |
Apache License 2.0 | GNU General Public License v3.0 only |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
parca-agent
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Flameshow: A Terminal Flamegraph Viewer
If that's true, you should probably update the docs. Everything I could find implied dotnet, jvm, python were still unsupported. For example, the roadmap section of the readme mentions most of these but nothing mentions dotnet. However I did find your tickets and a demo being merged in which makes it seem maybe supported?
Ticket: https://github.com/parca-dev/parca-agent/issues/161
Demo: https://github.com/parca-dev/parca-demo/pull/18
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How to troubleshoot memory leaks in Go with Grafana Pyroscope
Couldn't see any advantages to this over https://github.com/parca-dev/parca-agent. Which uses eBPF so it can be used with non-instrumented apps and code paths.
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Frame pointers vs. DWARF – my verdict
The pervasive lack of frame pointers is the reason why we've developed a custom format derived from DWARF unwind information thanks to some insights: DWARF unwind information is incredible flexible, it supports many arches and allows restoring any arbitrary register. But we only need 3: the frame pointer, the stack pointer, and in non-x86 the return address.
In addition, this encoding doesn't use that many bytes, but unfortunately reading and parsing that information is quite expensive.
For that reason I've developed a new unwinder that uses custom unwind information derived from DWARF (https://www.polarsignals.com/blog/posts/2022/11/29/profiling..., previously discussed in https://news.ycombinator.com/item?id=33788794) that runs in BPF. This new compact representation can be binary searched easily and each unwind row has a size of 16 bytes. I are currently working on reducing it down to ~10 bytes.
All the code is fully OSS (Apache 2.0 for userspace and GPL for BPF), and part of the Parca project (https://github.com/parca-dev/parca-agent).
We've also given some talks in FOSDEM going deeper into how we made it scale for many big processes.
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Dwarf-Based Stack Walking Using eBPF
I find this surprising! Was this for off the shelf applications or some custom binaries?
As mentioned above, we see DWARF expressions such as `DW_CFA_def_cfa_expression` on the regular. See the "Test Plan" section and commit messages of the PR that introduced support for this particular opcode [0]
[0]: https://github.com/parca-dev/parca-agent/pull/1058
- Parca Agent rewrites eBPF in-kernel C code in Rust (using Aya-rs)
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Fantastic Symbols and Where to Find Them - Part 2
Let's see an example perf map file for NodeJS. The runtimes out there output this file with more or less the same format, more or less!
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Fantastic Symbols and Where to Find Them - Part 1
The good news is we got you covered. If you are using Parca Agent, we already do the heavy lifting for you to symbolize captured stack traces. And we keep extending our support for the different languages and runtimes.
austin-tui
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Flameshow: A Terminal Flamegraph Viewer
There is a "live" flamegraph TUI that uses Austin for those interested in Python profiling https://github.com/P403n1x87/austin-tui. The data collected can be exported and then converted into pprof, and analysed further with flameshow etc...
- Live flame graph rendering in the terminal
- Live flame graphs rendering in the terminal
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Austin – Python Frame Stack Sampler (or zero-instrumentation profiling) 2.1.1
- Scoop
Austin is also simple to compile from sources as it only depends on the standard C library, if you don't have access to the above-listed repositories.
This new release of Austin brings enhanced support for many Python binary distributions across all the supported platforms, as well as a bugfix for the line number reporting. If you rely on Austin 2, upgrading to the latest version is strongly recommended.
Let me also remind you of some of the other existing Python tools powered by Austin, which have also seen new releases in the past few days, and that are easily available from PyPI:
https://github.com/P403n1x87/austin-tui
What are some alternatives?
kubectl-flame - Kubectl plugin for effortless profiling on kubernetes
parca-demo - A collection of languages and frameworks profiled by Parca and Parca agent
ebpf - ebpf-go is a pure-Go library to read, modify and load eBPF programs and attach them to various hooks in the Linux kernel.
rbspy - Sampling CPU profiler for Ruby
perf-map-agent - A java agent to generate method mappings to use with the linux `perf` tool
ruby-prof - A ruby profiler. See https://ruby-prof.github.io for more information.
pwru - Packet, where are you? -- eBPF-based Linux kernel networking debugger
ansible-trace - Visualise Ansible execution time across playbooks, tasks, and hosts.
Musort - A command-line tool for effortlessly organizing and renaming your music files based on metadata
go-profiler-notes - felixge's notes on the various go profiling methods that are available.
textual-web - Run TUIs and terminals in your browser