Gisia – A Lightweight Self-Hosted DevOps Platform

Hacker News

Hi HN, I've been building Gisia – a lightweight, self-hosted DevOps platform for individuals and small teams. It's simpler, more lightweight and you can self-host. Key Features: - Git repository hosting with SSH and HTTP access - CI/CD pipelines with YAML configuration - Issue tracking - Built with modern Rails stack (Rails 8, PostgreSQL, Stimulus/Turbo, Tailwind CSS) Why Gisia? - Lightweight with minimal dependencies - Developer-first design - Fully open-source and auditable - You own your data Current Status: Currently in Alpha with core features complete. Merge requests and notifications are planned. Try It Out: You can take Gisia for a test drive by following the quick start guide in the README. Feedback and contributions welcome!

Visit product View on Hacker NewsOct 25, 2025

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Actual performance

2points

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Did not reach leaderboard

Launch Intel predictions

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

81%81% 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: ide, pipe, io · Missing: https docs, excited, just released

75%75% 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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: platform, host · Missing: plus, intuitive, reviews

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

35%35% 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

15%15% 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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