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HertzBeat – An open-source, real-time monitoring system

Hacker News

HertzBeat – An open-source, real-time monitoring system

Hi everyone! Very happy to be able to recommend an open source project here. Hertzbeat is an open-source, real-time monitoring system with custom-monitor and agentless. Support web service, database, os, middleware and more. Here’s a video of show: https://youtu.be/eb_Nosl9fZY . Very open to feedback. github: https://github.com/dromara/hertzbeat home: https://hertzbeat.com/en/ Very welcome to use and give us a star! Thanks!!!!

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Actual performance

3points
1comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide · Missing: https docs, excited, just released
52%52% 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 HuntOn track for Day 1 leaderboard · Strong signals: agent, open · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
28%28% 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
15%15% 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
9%9% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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