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A self hosted alternative to Ngrok

Hacker News

A self hosted alternative to Ngrok

Hi! I am sharing this because it may be useful to others. I created a simple Docker image that lets you easily expose a web app running locally on your dev machine to the Internet, via a proxy server. It is a self hosted alternative to something like Ngrok, which is a paid service if you use custom domains. A small server is cheaper than Ngrok (I use Hetzner Cloud and the cheapest server costs me 3€ per month). I use this method in particular to test HTTP verification with Let's Encrypt for a SaaS app running on my Mac. Hope this is useful :) Code: https://github.com/vitobotta/docker-tunnel Blog post: https://vitobotta.com/2019/06/29/self-hosted-alternative-to-...

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Hacker NewsStrong engagement from HN community · Strong signals: 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.
Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting
60%60% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, dock, grok · Missing: agents, macos, agent
56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: saas · Missing: arr, mrr, revenue
19%19% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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