An immutable ostree-based Arch Linux image

Hacker News

i've been a big fan of fedora's atomic distros and i decided to make my own but arch based to get the best of both worlds, which is kind of funny now because it looks exactly like silverblue. is it worth it? not sure, but it's been a interesting experience – and it's usable as a daily driver if your specs match. worth noting that because of the constraints of the setup you can develop something similar on your main machine without any realistic possibility of data loss since you never really touch the bootloader or the filesystem (partitioning and so on).

Visit product View on Hacker NewsDec 27, 2025

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Hacker NewsStrong engagement from HN community · Strong signals: filesystem, ide, io · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% 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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac · Missing: agents, macos, agent

38%38% predicted probability of success on Product Hunt, 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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