Osync – A Git and rsync tool for local syncing and backups

Hacker News

Hey everyone, I made a small tool called osync, a setup that uses Git and rsync to sync and back up directories between devices. It started as a personal experiment to sync my Obsidian notes between my PC and phone without relying on cloud storage or overcomplicated tools. I thought it would be simple, just SSH and rsync, but it turned into a great learning experience. Now the script can, once SSH, systemd, and the works are set up, automatically sync between two computers reliably while also backing up to a Git repository. GitHub: https://github.com/Kena-Njonge/osync I also wrote a blog post https://open.substack.com/pub/kenakiruri/p/how-i-backup-and-... that goes over the motivation and acts as a tutorial if you want to use the tool to sync your Obsidian vaults. It also covers some of the differences between this setup and other alternatives. Would love to hear your thoughts, especially on how I could improve it from a software engineering perspective. Thanks!

Visit product View on Hacker NewsOct 27, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: computer, notes, open · Missing: mac, agents, macos

75%75% 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.

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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

45%45% 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 · Missing: plus, platform, intuitive

45%45% 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

10%10% 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.

Correct prediction on native model

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