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Reli – a sampling profiler and VM state inspector for PHP

Hacker News

Reli – a sampling profiler and VM state inspector for PHP

I showed an earlier version of this here a bit over two years ago. Since then, Reli has grown a lot. Reli is a sampling profiler and VM state inspector for PHP, written in PHP, that inspects running PHP processes from the outside. In 0.12.0, tracing, memory analysis, monitoring, and runtime inspection all expanded quite a bit. I would be especially interested in feedback on whether the memory-analysis, watch, and variable-inspection direction looks useful.

Visit product View on Hacker NewsApr 30, 2026

Actual performance

2points

Did not reach leaderboard

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Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

42%42% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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

10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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