I made a desktop Mac App Store app for fun

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So I made a Mac OS X app for fun with a couple of friends: Graphical Network Monitor https://itunes.apple.com/us/app/graphical-network-monitor/id1002978158?ls=1&mt=12 The idea was inspired from the website I wrote in my college networking class, yougetsignal.com. Basically the app does a very fast kernel-level netstat of all of the active connections on your computer, geo-locates each remote IP address you are connected to, and drops the icon of each app connection on the map. I have found some surprising discoveries, mainly around programs maintaining persistent connections to various places in the world (e.g., Sublime Text initiates and holds onto a connection to Texas at all times). It's also just mind-blowing to see how much crap your computer connects to all of the time with even just basic browsing. There's a Windows version here: http://www.graphicalnetworkmonitor.com/ We are charging $4.99 based on some price testing we did on the Windows version. Right now the Mac app is #86/100 out of all paid Mac apps which is pretty fun. If you check out the app please send feedback and let me know what else you would like to see in the app, right now it is very simple and fun utility but I suppose it could grow to do more things...

Visit product View on Hacker NewsAug 27, 2015

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

82%82% 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.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% 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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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