Fly.io Lemmy

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Fly.io Lemmy

Like many others, I'm migrating from reddit to Lemmy. I figured it would be more fun to host a Lemmy instance myself, but I don't want to manage uptime on a VPS... and Kubernetes seemed a little too heavy for the task at hand. So, I wrote a tool that lets you quickly create a Lemmy instance on fly.io. It's pretty naive but it will get you started and it should just work:tm:. Note I'm not sure if this fits in fly.io's free tier. I had to up the size of the postgres database and pict-rs host to 512MB, but I anticipate it being pretty cheap at least.

Visit product View on Hacker NewsJun 12, 2023

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4points

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Did not reach leaderboard

Launch Intel predictions

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

75%75% 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

70%70% 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: started · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host · Missing: plus, platform, intuitive

47%47% 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

17%17% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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