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Deploy to cloud

Run your flows on Repster Cloud: your schedules fire without your machine on, and each run gets its own isolated worker, created on demand. The pipeline code is exactly what you ran locally.

Prerequisites

  • A working local flow (see Quickstart)
  • A Repster account (you'll create one during rp login if you don't have one yet)

1. Authenticate

rp login

Repster asks for your email and a password. If it doesn't recognize the address it offers to create an account, then asks you to confirm the password — at least 12 characters — and whether you're starting a new organization or joining one you'll be added to. Your credentials are saved to ~/.repster/config.toml.

You never need to run rp login before deploying; any cloud command that needs auth will walk you through it inline. To drive it from a script or an agent instead, see Non-interactive login.

If your organization has not yet accepted the Repster Cloud terms, you'll be shown links to the Design Partner Agreement and Privacy Policy and asked to type accept before the command continues. Only an org admin can accept, and it's a one-off — see rp terms.

2. Push secrets

If your pipeline uses environment variables (API keys, database credentials), push them before deploying:

rp secrets push

This reads your .env file and stores the values, encrypted, in the Repster Cloud vault. See Manage secrets for details.

3. Deploy

rp deploy

Repster packages your project (source files + uv.lock), uploads it, and registers your flows. Deployments are immutable; see How Repster works.

4. Trigger a cloud run

rp run --cloud hackernews_top

The run is dispatched to an isolated cloud worker. You get the run ID immediately; the flow executes asynchronously.

5. Monitor the run

rp status                         # last N runs (local + cloud, combined)
rp logs --run <run-id>            # full log output

6. View in the UI

Log in to the Repster Cloud UI (cloud.repster.online) to see runs, logs, deployments, and secrets in one place.

Re-deploying

After changing your pipeline code:

rp deploy        # upload new version
rp run --cloud hackernews_top   # runs the latest deployment

Old deployments are preserved; runs always reference the deployment they were dispatched against.

Next steps