Ts

Tspages – static site hosting platform for your Tailscale network

Hacker News

Tspages – static site hosting platform for your Tailscale network

Hey HN! This is a small side project I'm currently working on. With tspages, you can quickly host static websites on arbitrary hostnames in your tailscale network. This is useful for internal documentation or tools that don't warrant their own server or k8s deployment, for example. I was frustrated with the other options - hosting on one of the public providers like Cloudflare Workers or Vercel means having to lock down auth and hope you never screw that up; hosting on an internal web server means you can't have speaking Tailnet names. So this is kind of a middle ground: tspages let's you create new static websites very easily, say `design-system.funky-animal.ts.net`: Simply drag-and-drop a folder, archive, or file or send it with curl, and the site will be up in a second. Deployments are archived, and you can easily switch to an older deployment via API or UI. Since tailscale requests carry identity, tspages checks authorization to create, deploy, or view sites against your tailnet policy: You can use an app capability to create different permissions for users or tags. This also allows for some very basic analytics for hosted sites. Finally, tspages allows to upload a config file alongside your assets to set some configuration parameters for the site, like enable SPA fallback routing, custom headers, or redirection targets. This project is very young, so there might be some rough edges, but it does work, runs stable, and the capability system is sound. Let me know what you think!

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new · Missing: mac, agents, macos
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
79%79% predicted probability of success on Indie Hackers, 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
72%72% 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 · Strong signals: users, para · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host, users · Missing: plus, intuitive, reviews
40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
20%20% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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