An Open-Source Platform for Raspberry Pi with Robust OTA Updates

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Over the last few weeks, I worked on a set of tools which enables (1) a modern workflow to build customized images for Raspberry Pi, (2) robust over-the-air updates with rollback support of the entire system, including firmware files, and (3) managed state which is preserved across reboots and updates. The goal is to have a reliable platform for creating Raspberry Pi-based products. The initial motivation for the project came from one of our customers who uses Raspberry Pi to control test benches for pedelecs. The entire project is open-source. Feel free to check it out and give it a try. The project is still in an early stage and I am eager to hear your thoughts and opinions. Also, feel free to ask any questions! :)

Visit product View on Hacker NewsJul 24, 2023

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

83%83% 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: including · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% 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 · Strong signals: platform · Missing: plus, intuitive, reviews

51%51% 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

38%38% 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

14%14% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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