Ma

Manage on-prem servers from my smartphone

Hacker News

Manage on-prem servers from my smartphone

Hi everyone, I've just released the public repository of RebootX On-Prem ( https://github.com/c100k/rebootx-on-prem ), letting anyone to connect and manage their infra on their smartphone. In my case the infra is pretty simple : 3 Raspberry Pi. But I'd love to have your feedback and see interesting use cases you could use this for. I have lots of ideas for the next steps. For example, creating a Prometheus integration as well. Looking forward to hearing from you and I would be glad to help if you encounter any issue getting started with the repo.

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Hacker NewsStrong engagement from HN community · Strong signals: just released, ide, io · Missing: https docs, excited, exist
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.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting
26%26% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
11%11% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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