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Pf

Pfelk, a customizable pfSense/OPNsense firewall visualization

Hacker News

Pfelk, a customizable pfSense/OPNsense firewall visualization

PFELK is a pfSense/OPNsense firewall traffic visualization solution based on ELK stack. It is a highly customizable tool that let’s you have extensive insight into your network traffic. Key points: - pfSense/OPNsense support - openVPN support - pfSense/Suricata/Snort dashboards with interactive Maps support (MaxMind GeoIp fields, src -> dest locations, Heatmap, etc.) - deploy with ansible-playbook, docker or script. https://github.com/3ilson/pfelk

Visit productView on Hacker NewsMar 22, 2020
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Actual performance

51points
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
55%55% 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 · Strong signals: vpn · Missing: supports, reddit linkedin, podcasting
53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: dock, visual, open · Missing: mac, agents, macos
39%39% 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
38%38% 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
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
10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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