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OneUptime – open-source observability platform

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OneUptime – open-source observability platform

We're building an open source observability platform - OneUptime ( https://oneuptime.com ). Think of it as your open-source alternative to Datadog, NewRelic, PagerDuty, and Incident.io—100% FOSS and Apache Licensed. Already using OneUptime? Huge thanks! We’d love to hear your feedback. Not on board yet? We’re curious why and eager to know how we can better serve your needs. What features would you like to see implemented? We listen to this community very closely and will ship updates for you all. Looking forward to hearing your thoughts and feedback!

Visit productView on Hacker NewsJan 15, 2025
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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, using, open · Missing: mac, agents, macos
88%88% 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 NewsStrong engagement from HN community · Strong signals: open source, ide, io · Missing: https docs, excited, just released
76%76% 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 · Missing: supports, reddit linkedin, podcasting
62%62% 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 · Missing: plus, intuitive, reviews
48%48% 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
34%34% 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
14%14% 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
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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