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I made a simple but powerful deployment tool

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I made a simple but powerful deployment tool

Been using it for about a year now in production, but rewrote it completely in golang. My first go project so far. I wanted to have something that would make my life easier. A lot of tools nowaday kinda push you towards functional deployments and that usually doesn't work for me since I like stuff like LiveView by Phoenix and Websocket stuff in general. Old vercel deployments back when they allowed to deploy docker containers was a godsend, but since they don't offer that anymore I had to use services like fly.io(which is amazing) or heroku. However I wanted something selfhosted that I could just grab any VPS and use it, not being reliant on any one party for hosting, CI\CD, maintanence or anything really and so far it's going great. Hosting some small to medium sized projects using this little fella. Would be cool if yall would look at it and tell me what you think. Comments on my code also would be very welcome, go turned out to be very cool and I wanna try more stuff with it I was thinking to maybe use docker swarm to make it horizontally scalable, but it feels like such an overkill, wdyt?

Visit productView on Hacker NewsMay 15, 2024
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5points
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
95%95% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: dock, using, code · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
66%66% 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 · Strong signals: host · Missing: plus, platform, intuitive
49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% 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
13%13% 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
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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