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title Self-hosting quickstart
description Get a managed self-hosted Oz worker running on Docker and route your first cloud agent run to it in under 10 minutes.
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Quickstart

Run your first Oz cloud agent on your own infrastructure in ~10 minutes using the managed architecture with the Docker backend — the default and fastest path to self-hosting.

:::note This quickstart sets up the managed architecture, where Oz orchestrates the agent and your worker provides the compute. Prefer a CLI-only path with no Docker requirement? Jump to the Unmanaged quickstart to run oz agent run directly on any host. :::

Prerequisites

  • Enterprise plan with self-hosting enabled — Contact sales if self-hosting is not yet enabled for your team.
  • A Linux machine with Docker — A VM, server, or local machine with the Docker daemon running Linux containers. Verify with docker info. Docker Desktop on macOS or Windows works for testing.
  • A team API key — In the Warp app, go to Settings > Cloud platform > Oz Cloud API Keys to create a team-scoped API key. See API Keys for details.
  • The Oz CLI (for routing a test run) — See Installing the CLI.

Run your first self-hosted agent

~10 minutes

1. Export your API key

Export the team API key so the worker container can authenticate to Oz automatically:

export WARP_API_KEY="your_team_api_key"

2. Start the worker

Run the oz-agent-worker container, mounting the host's Docker socket so the worker can spawn task containers. Choose any --worker-id meaningful for your team — you'll use this value to route tasks to this worker.

docker run -v /var/run/docker.sock:/var/run/docker.sock \
  -e WARP_API_KEY="$WARP_API_KEY" \
  warpdotdev/oz-agent-worker --worker-id "my-worker"

Expected outcome: The worker connects to Oz and begins listening for tasks. You should see log output confirming the connection (something like Connected to Oz / Waiting for tasks).

:::caution For production deployments, pin to a specific image digest (e.g., warpdotdev/oz-agent-worker@sha256:...) instead of the latest tag. :::

3. Route a run to your worker

In a separate terminal on any machine with the Oz CLI, route a cloud agent run to your worker by passing --host with the worker ID you chose:

oz agent run-cloud --prompt "List the files in the current directory" --host "my-worker"

Expected outcome: Oz accepts the task, routes it to your worker, and the worker spawns a Docker container to execute the agent. You'll see the run appear in the Oz dashboard with status moving from QUEUED → INPROGRESS → SUCCEEDED.

4. Verify the run

Open the Oz dashboard, find the new task, and confirm the session transcript shows the agent running against your worker. You can attach to the session at any time via Agent Session Sharing to monitor or steer it.

Next steps

  • Unmanaged quickstart — ~5-minute CLI-only path: run oz agent run in your CI, Kubernetes pod, or dev box with no worker daemon and no Docker requirement.
  • Managed: Docker — Full Docker backend setup, including private registries, volume mounts, and runtime configuration.
  • Environments — Define a repository, Docker image, and setup commands so agents have a reproducible workspace for every run.
  • Routing runs to self-hosted workers — How to route tasks from schedules, integrations (Slack, Linear), the API, and the Oz web app.
  • Managed: Kubernetes — Deploy workers into a Kubernetes cluster with Helm.
  • Self-hosted worker reference — All CLI flags and config file options.

Troubleshooting

Worker won't start
Verify Docker is running (docker info) and that the daemon platform is linux/amd64 or linux/arm64. Musl-based (Alpine) worker hosts are not supported.

Worker won't connect
Verify your API key has team scope. Ensure the machine has outbound internet access to oz.warp.dev:443. Increase log verbosity with --log-level debug to see connection details.

Task stays queued and never runs
Confirm the --host value you passed to oz agent run-cloud matches your --worker-id exactly (case-sensitive). Check that the worker's team matches the team creating the task.

For more, see Troubleshooting.