Video demo of “go on rails” framework

Hacker News

Been working on this framework for a few years. I like to call it the "go on rails" framework. I use this in production for several clients. It runs so nicely on the google compute free tier VM. You get a 30GB hard drive, 1GB ram, and two AMD EPYC 7B12 2250 MHz processors which is plenty for a little golang program that just serves rendered HTML from database queries. I run postgres on the same VM to keep it free. Still plenty of space memory and cpu wise. (I also use that 30 GB hard drive as a "bucket" to avoid any cloud storage fees for images, etc.) Here is a 3 min demo of the framework: https://www.youtube.com/watch?v=KU6-BTxQoCA

Visit product View on Hacker NewsSep 9, 2023

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

73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% 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

31%31% 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

23%23% 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

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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