N1netails – lightweight, self-hosted alerting platform for developers

Hacker News

I built N1netails, a lightweight, self-hosted alerting platform for developers. Features: - Sends alerts to Discord, Slack, Telegram, MS Teams, and email - Simple Spring Boot backend + Angular frontend - Token-based API for integrating alerts from your apps - Optimized for solo developers and small teams - Self-hosted, lightweight, easy Docker setup Dashboard: https://app.n1netails.com Docs: https://n1netails.com GitHub: https://github.com/n1netails/n1netails I’d love feedback from the community on features, usability, or anything else!

Visit product View on Hacker NewsNov 25, 2025

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1points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, apps, dock · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

49%49% 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

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

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

40%40% 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

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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