deployment/k8s/deployments/sandbox-deploy.yaml pulls arc53/docsgpt-sandbox,
which has never been pushed anywhere: Compose builds the runner from the
checkout (`build: ./sandbox`), but Kubernetes cannot build, so enabling code
execution on a cluster failed on an image that does not exist.
Build and push it like the other two images: `develop` on a push to main that
touches deployment/sandbox, and `<version>` plus `latest` when the release
workflow calls it. Release and develop live in one file here rather than two,
because the runner changes rarely and the only difference is which tags move.
The tag comes from the inputs and the release payload, not from
`github.event_name`, which is `push` when backend-release calls this.
Run each kernel under a scrubbed environment so untrusted code can never read
the host's secrets. A custom 'docsgpt-python' kernelspec launches ipykernel
through a wrapper that keeps only what the kernel needs (PATH, HOME, LANG, and
the Jupyter runtime/data dirs), dropping API keys, tokens, the database URL, and
the gateway token. The app selects this kernel by name via SANDBOX_KERNEL_NAME,
so the distinct name is never shadowed by the stock python3 spec. Per-session
workspaces are created mode 0700 (defense in depth under the shared uid). The
README documents the runner as a single trust domain and points to the Daytona
backend for per-tenant isolation.
Expose a user's artifacts through the MCP server as readable resources: each is
listed under an artifact:// URI with its mime type and read on demand as inline
text or a base64 blob, bounded by a size cap and scoped strictly to the owning
principal resolved from the request's API key, so no artifact is served across
tenants. Ship the network-level egress controls the sandbox runner needs but
cannot self-apply: a Kubernetes NetworkPolicy that allows public egress while
denying RFC1918, link-local, and cloud-metadata ranges, an optional
docker-compose egress overlay, and runner network-hardening docs.
Alex