A

A tool to redirect traffic from remote K8s service to local

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A tool to redirect traffic from remote K8s service to local

Hello everyone! Behold! My crippled golang skillz have developed a tool that allows you to forward traffic from a k8s service to your laptop (or anything really ;-). Secure tunnels are involved! It seems to be a common pattern to use and deploy big apps in remote k8s environment which are either vendor locked into some cloud services that require secrets or simply unfit to run locally. This simple apps, allows you to redirect traffic from existing k8s service straight to your laptop (or whatever else really!). It's easy, secure, open source and it works. PRs and Issues are very welcome! :-)

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Actual performance

4points
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% 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: apps, open · Missing: mac, agents, macos
65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, open source, existing · Missing: https docs, excited, just released
65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: apps · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% 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
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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