Cloud GeoIP via DNS Test Tool

Hacker News

Made a configuration and guide to configure and use 3 clouds's DNS services to see where clouds such as GCP, Azure, and AWS think some computer is if some DNS names are dig'd up. I've already deployed this so it's already usable. To be honest, I doubt this is useful for anything beyond curiosity and remediation if you see any issues is likely impossible. Kind of sadly useless I suppose. Anyway, you don't need any tools on your computer except dig to resolve some CNAMEs. The readme is a guide.

Visit product View on Hacker NewsJan 28, 2025

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

37%37% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

32%32% 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

11%11% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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