I built a face-to-face video chat app with Rails 6

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DISCLAIMER: This tutorial is not for beginners. Want to know how to build apps like skype, zoom etc... using Ruby on rails 6? I got you!! Building a video chat feature on a ruby on rails application is not an easy thing to do. That’s one of the reasons why I decided to do it, another reason being that I didn’t want to build another blog, todo-app etc… I wanted something challenging. You can check the app on heroku at https://dev-video.herokuapp.com/. For a demo, you can either do it yourself (by logging into two separate accounts on different browsers), or check this small demo on youtube at https://www.youtube.com/watch?v=WXouJ8w7rQg . Here is a link to the first 7 chapters of the tutorial: https://www.dropbox.com/s/2aqdsvm721tr01s/Ebook2020.pdf?dl=0 . You can get the full ebook on Gumroad at https://gumroad.com/l/lNEhE If you want to follow along with this tutorial, you are going to need a few things: Ruby 2.7 Rails 6.0.2 AWS S3 bucket AWS credentials (access_key_id and secret_access_key) Tokbox credentials HAPPY CODING!!!

Visit product View on Hacker NewsJan 24, 2020

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Did not reach leaderboard

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

74%74% predicted probability of success on Indie Hackers, 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: ide, io · Missing: https docs, excited, just released

59%59% 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 HuntUnlikely to reach the leaderboard · Strong signals: apps, using, coding · Missing: mac, agents, macos

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

TrustMRRLess likely to generate early MRR · Strong signals: apps, video, para · 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

39%39% 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

20%20% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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