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An open-source monitoring tool like zabbix or prometheus

Hacker News

An open-source monitoring tool like zabbix or prometheus

Hi guys! Very happy to be here to introduce our new open source project - HertzBeat Hertzbeat is an open-source, real-time monitoring tool which we speed one more year to create it. Monitor+Alerter+Notify all in one. With custom-monitor and agentless. Support monitoring web service, database, os, middleware, cloud-native, network and more. We make protocols such as `Http, Jmx, Ssh, Snmp, Jdbc` configurable, and you only need to configure `YML` online to collect any metrics you want. Do you believe that you can immediately adapt a new monitoring type such as K8s or Docker just by configuring online? Just one command to get started: docker run -d -p 1157:1157 --name hertzbeat tancloud/hertzbeat Welcome to use and star. github: https://github.com/dromara/hertzbeat home: https://hertzbeat.com/

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, dock, new · Missing: mac, agents, macos
68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: open source · Missing: https docs, excited, just released
64%64% 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 HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
49%49% 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
35%35% 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
12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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