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Self-hosted dev sandboxes with preview URLs (Docker, Go, no K8s)

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Why This Matters

This open-source solution simplifies the creation of isolated, self-hosted development environments with instant previews, enabling developers and AI app builders to deploy and test applications rapidly on their own servers. Its lightweight design, leveraging Docker and minimal dependencies, makes it accessible and cost-effective, especially for small teams or individual developers. This innovation empowers the tech industry by democratizing rapid app development and fostering greater control over deployment environments.

Key Takeaways

sandboxed

The open-source engine for AI app-builder products.

Give every user an isolated cloud dev environment, a built-in coding agent, and a live preview URL — self-hosted, on one machine, in one command.

What is sandboxed? (start here)

Think of the apps where you type "build me a todo app" and seconds later a working website appears at its own link — like Lovable, Bolt, v0, or Replit. sandboxed is the open-source backend that makes that possible, running on your own server.

Here's what it does, in plain terms. You send it one HTTP request, and it:

Creates a sandbox — a private, isolated Linux container (its own filesystem, its own memory limits), so one user's code can never see or break another's. Runs an AI coding agent inside it — you give it a prompt, and it writes the code into that sandbox. (The OpenCode and Claude Code CLIs come pre-installed.) Gives the app a live URL — the dev server running inside the sandbox is instantly reachable at a shareable preview link.

POST /sandbox → a private, isolated container spins up POST .../tasks → an AI agent writes an app inside it http://<id>.preview... → that app is live at its own URL

It's also cheap to run: a sandbox goes to sleep when nobody's using it (freeing memory) and wakes up the instant someone opens its link again — files are saved on disk the whole time. So one ordinary server can hold many users instead of needing one virtual machine each.

Under the hood it's deliberately small and easy to understand: one Go program that tells Docker what to do, with Traefik handling the URLs and SQLite as the database. No Kubernetes, no separate database server, no message queue — you could read the whole thing in an afternoon.

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