Connect Lakeshore to DreamLake
Use this guide when a Lakeshore server is already running. You need its HTTPS URL, a Lakeshore namespace, an access token for that namespace, and the DreamLake CLI.
If you are hosting the server yourself, first follow Setting Up Lakeshore Service. If someone else operates it, ask them for the URL, namespace, and token.
Connecting saves a server connection in DreamLake. It does not start the server or enroll workers. The Python SDK quick start can use the service directly without this connection.
1. Get an access token
Already have a token? Continue to step 2.
For server administrators: after logging the Lakeshore CLI into the intended server and namespace, mint a separate token for DreamLake:
Use the same admin token configured on the server. Save the printed client token; it is shown once. Keep LAKESHORE_URL unset so the CLI uses the server and namespace from your saved login.
2. Connect the server
With the DreamLake CLI installed:
Replace the URL and Lakeshore namespace with the values from your administrator. Paste the access token at the hidden prompt. DreamLake verifies the connection and saves the credential in Vault.
--prefix lab is the connection's name in DreamLake. --lakeshore-namespace lab is the namespace on the server; the two names can differ.
The connection belongs to your active DreamLake namespace. To use an organization, add --namespace your-org to the mount command and every check below.
3. Check the connection
inspect should report a healthy connection. Empty queues, workers, and jobs are normal before you enroll workers or submit work.
Disconnect later
This removes the DreamLake connection. It retains Vault entries and leaves the server running.