DockMate – Terminal UI for Container Management

Hacker News

Build Dockmate - Docker/Podman containers manager TUI application in Go using bubble-tea TUI framework. Features: - Container management (start/stop/restart/remove, logs) - Real-time container monitoring (CPU, memory, disk I/O, etc.) - View/Hide columns (Memory, Cpu, Net I/O, etc.) - Compose project grouping - Podman runtime support (switch easily) - Persistent settings (YAML config) - Info/Help panels with shortcuts - Configurable Interactive Shell (/bin/sh, /bin/bash, etc.) - Homebrew support - One command-line installation Works on both Linux and macOS!! Demo Gif: https://github.com/shubh-io/DockMate/blob/main/assets/demo.g... Github: https://github.com/shubh-io/DockMate

Visit product View on Hacker NewsDec 29, 2025

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Actual performance

5points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

72%72% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

53%53% 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

34%34% 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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

12%12% 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.

Incorrect prediction on native model

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