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Kadugu VPN – QUIC, TCP Split connection approach for blazing speed

Hacker News

Kadugu VPN – QUIC, TCP Split connection approach for blazing speed

I’ve been working on Kadugu, a lightweight and decentralized(libp2p-rust) VPN designed for self-hosting on a VPS or setting up between friends. Key Features: Optimized for Performance: Kadugu uses the QUIC protocol along with a split connection approach (QUIC+TCP) to handle unstable networks. This results in faster speeds and more reliable connections, especially when dealing with variable network conditions. Lightweight Codebase: The entire project is under 1,000 lines of code. Just download the single binary, run it, and share your Peer ID to connect.

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Actual performance

3points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: vpn · Missing: supports, reddit linkedin, podcasting
70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: 000, io · Missing: https docs, excited, just released
66%66% 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 · Strong signals: host · Missing: plus, platform, intuitive
49%49% 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
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: single, code · Missing: mac, agents, macos
45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% 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
6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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