I built a tool to manage deployments across your VPS through a web UI

Hacker News

There are plenty of ways to deploy your apps. PaaS options like Vercel or Netlify are convenient but can get pricey as projects scale. VPS hosting is cheaper, but setting it up (Linux, networking, SSL, etc.) can be daunting. That’s why glueh-wyy-huet ( https://github.com/glueh-wyy-huet ) and I ( https://github.com/biersoeckli ) built QuickStack during our bachelor studies at Eastern Switzerland University of Applied Sciences. QuickStack simplifies deployment by letting you deploy directly from a Git repo or Docker registry to any VPS. It’s free, open source, and installs with a single command on your VPS. Unlike great tools like CapRover, Easypanel or Coolify, QuickStack is built on lightweight Kubernetes (k3s) and uses Longhorn for distributed storage, enabling multi-VPS clusters managed through a single UI. Persistent app volumes are distributed across the cluster automatically. Features include Git deploys, live logs, web-terminal, SSL cert generation, backups, monitoring, and single-VPS setups for smaller needs. We’d love your feedback. Check it out on https://quickstack.dev and have fun deploying with QuickStack!

Visit product View on Hacker NewsJan 28, 2025

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

80%80% predicted probability of success on Product Hunt, 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: open source, 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 · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

27%27% 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

16%16% 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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