Customized for your Company

Deploy a pinned Cloudflare OS release with branding, sign-in, integrations, routes, and upgrades under your control.

[!IMPORTANT] Cloudflare OS is early-access software. Pin upstream releases, review changes, and verify the trust boundary before every production upgrade.

Four steps

1. Install the dependencies and run pnpm exec wrangler login.
2. Fill in deployment.jsonc: account ID, Worker names, hostname, Access audience, admin emails.
3. Run pnpm check, then pnpm deploy.
4. Open /admin and set the site name, logo, and accent color; branding needs no redeploy.

Deploy and Customization expand each step. Everything else on this page is optional reading.

Overview

This repository adds deployment controls around a pinned Cloudflare OS release without modifying the upstream source.

Architecture

The deployment is six Workers. A router owns the public route and serves the frontend, proxying /api to the Workshop backend and /gatekeeper/<name> to whichever Gatekeeper the binding name matches; the Workshop, the Context, Scheduler and custom Gatekeepers, and the Error Reporter sit behind it with no route of their own, reachable only over service bindings.

The deploy command derives temporary Wrangler files from upstream base configs, builds the frontend in Cloudflare Access mode, deploys the private Error Reporter, the Gatekeepers and the Workshop before the router that binds them, and removes generated files even on failure. Secrets never enter tracked configuration.

If you only want branding

A hosted flow deploys the same upstream release to your Cloudflare account without this repository. It builds nothing locally, configures sign-in and your admin emails for you, and leaves the whole /admin surface intact: site name, logo, accent color, announcements, agent instructions, featured blueprints, and which connectors your users can reach. Built-in Gatekeepers such as GitHub and Google are still yours to connect with your own OAuth credentials.

Anything past that needs your own code or settings, which is what this repository is for: custom Gatekeepers, customized error reporting, your own Worker names, reusing storage you already have, choosing how much logging to keep, and a pinned version you upgrade when you decide. Hosted deployments also run on a workers.dev address, so deploy from here if you want the app on your own domain, or the email Gatekeeper, which needs a zone. Come back when branding stops being enough.

Deploy

1. Prepare the workspace

Install Node.js 24.19 or newer (the deploy scripts are TypeScript run directly by node), pnpm 11.17, and authenticate Wrangler:

git submodule update --init
pnpm install
pnpm --dir cloudflare-os install
pnpm exec wrangler login

Your account needs Workers, KV, R2, Browser Rendering, and Dynamic Worker Loaders. It also needs Workers AI and AI Gateway, which the default model catalog runs on; only turning that catalog off makes them dispensable. Artifacts is optional.

2. Configure sign-in

Cloudflare OS supports several sign-in methods. This starter deploys Cloudflare Access mode, which verifies identity before a request reaches the Worker. See Sign-in methods for the alternatives and what switching involves.

1. Choose a public hostname in an active Cloudflare zone, such as os.example.com.
2. Create a self-hosted Access application for that hostname.
3. Copy its application audience tag.
4. Open deployment.jsonc and replace the active placeholders. Every control is annotated in place.

The hostname belongs to the router, the only Worker here with a public route. Wrangler creates its DNS and TLS at deploy time. For an evaluation without a zone, switch the annotated route to { "workersDev": true } and set publicBaseUrl to the resulting origin.

3. Validate and deploy

pnpm check
pnpm deploy

With resource values left as null, Wrangler creates the three KV namespaces and R2 bucket automatically and reconnects them on later deploys. Set explicit IDs or a bucket name when the deployment must reuse existing resources.

A Workers AI model catalog is enabled by default and needs no API token: the Workshop reaches AI Gateway over its WORKERS_AI binding, which is pre-authenticated inside your account. See AI models to add providers, change the gateway, or turn the catalog off.

Git-backed Context collections are disabled by default. Accounts with Artifacts access can enable them in context.artifacts; see Context Artifacts.

Backend error reporting is enabled without a vendor account. Explicit upstream issue events become structured logs in the private Error Reporter Worker; see Observability and error reporting.

4. Verify the deployment

• Open the router's hostname and confirm Access signs in with the expected identity, and that it is the only public route into the deployment.
• Open /admin, confirm the email is an administrator, and set Context, Scheduler and Custom Gatekeepers to disabled, optional, or enabled.
• If Context Artifacts is enabled, create a Git-backed collection and confirm its repository can be populated and refreshed.
• Enable the Custom Gatekeeper, ask for deployment information, and confirm its read appears as an observation.
• Open the Error Reporter Worker's Workers Logs and verify its structured error_report query surface.
• Ask an agent to schedule something a few minutes out, and confirm it runs — that exercises the Scheduler Gatekeeper end to end.
• Review logs for the router, Workshop, Context, Scheduler, custom Gatekeeper, and Error Reporter Workers.

Customization

The complete control reference and recipes live in Customization. The upstream write-gatekeeper skill covers richer integrations.

Operations and upgrades

• Stream production events with wrangler tail.
• Triage explicit failures and choose export destinations with the observability guide.
• Roll a Worker back from its dashboard deployment history or with wrangler rollback.
• Follow the upgrade checklist before changing the pinned submodule.
• Review the upstream Cloudflare OS documentation and release history before adopting behavior changes.

Moving here from the hosted deploy (os.cloudflare.app/deploy)

Ejecting an instance created by the hosted flow means redeploying over Workers that already hold your data. Worker names, storage IDs, the public URL, and AI Gateway all have to be carried across by hand, and each one fails quietly if it is not: the deploy succeeds against empty storage. Migrating from the hosted deploy is the checklist.