NeoHtop – System Activity Monitoring on Steroids

Hacker News

NeoHtop is A modern, cross-platform graphical system monitor built on top of Svelte, Rust, and Tauri. featuring: Real-time process monitoring CPU and Memory usage tracking Beautiful, modern UI with dark/light themes Advanced process search and filtering Pin important processes Process management (kill processes) Sort by any column Auto-refresh system stats Search for processes by name, command, or PID. Use commas to search for multiple terms simultaneously. Regular expressions are supported for advanced filtering. Examples: arm, x86: Returns processes with "arm" or "x86" in the name or command d$: Lists daemons (processes ending with 'd') ^(\w+\.)+\w+$: Shows processes with reverse domain name notation (e.g., com.docker.vmnetd)

Visit product View on Hacker NewsNov 28, 2024

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

76%76% 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: dock, activity · Missing: mac, agents, macos

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

11%11% predicted probability of success on BetaList, 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.

Incorrect prediction on native model

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