Fw

Fwtui – A terminal UI for managing UFW (built with Bubble Tea)

Hacker News

Fwtui – A terminal UI for managing UFW (built with Bubble Tea)

I recently started writing Go professionally, after spending several years working mostly in Elm. Coming from Elm, I was naturally drawn to the Bubble Tea framework because of its Elm-like architecture and functional style. That made it a great fit for a hobby project to deepen my Go knowledge. The result is fwtui – a terminal UI for managing UFW (Uncomplicated Firewall) on Linux. What it does: Browse, add, and remove firewall rules Easily apply popular default profiles (e.g., SSH, HTTP, PostgreSQL) or create a custom one Understandable ports syntax with TCP/UDP support and range validation No mouse needed – works great over SSH Built entirely in Go with a focus on simplicity and TUI usability Repo: https://github.com/Beny406/fwtui Would love to hear your feedback – especially from other Go or Elm folks!

Visit product View on Hacker NewsMay 25, 2025

Actual performance

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2comments

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Launch Intel predictions

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

65%65% 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

64%64% 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 · Missing: https docs, excited, just released

57%57% 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

42%42% 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

37%37% 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

16%16% 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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