Pyroscope-rs a multi-language profiler built with Rust

Hacker News

The project started originally as a facade for pprof-rs to profile Rust applications and send data to a Pyroscope Server. It has then evolved to have its own internal timer, session manager, Backend interface and FFI support (for Python and Ruby). There are some light technical details here: https://github.com/pyroscope-io/pyroscope-rs/wiki/Technical-... The project is open source and can be explored on Github: https://github.com/pyroscope-io/pyroscope-rs . It's probably only relevant if you are interesting in profiling, observability and Rust!

Visit product View on Hacker NewsAug 9, 2022

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Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released

72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting

47%47% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: open · Missing: mac, agents, macos

45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

29%29% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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