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Troubleshooting

Tdarr_Node - Server not alive IP:xxx PORT:xxx​

This is normally a firewall or networking issue.

First, navigate to the Tdarr Server IP:PORT/api/v2/status address in the browser and check it's running. E.g. localhost:8266/api/v2/status. You should see some status details:

{
    "status":"good",
    "isProduction":true,
    "os":"win32",
    "version":"2.00.18",
    "uptime":346
}

Try putting the local IP address of the server when setting serverIP in the Node Config instead of using localhost or 0.0.0.0.

If the Server and Node are on different machines, make sure the Node can connect to the Server on port 8266 (or your configured serverPort). The Node initiates this connection and does not require an inbound port.

Node socket auth failed​

When authentication is enabled, a Node needs a valid API key to connect. If it doesn't have one, it won't show on the Tdarr tab and the Server logs one of the following:

Node socket auth failed: No users
Node socket auth failed: No auth token provided
Node socket auth failed: Invalid API key
  • No users: no account has been created yet. Open the web UI and create one.
  • No auth token provided: the Node has no apiKey set.
  • Invalid API key: the Node's apiKey doesn't match any key on the Server, for example because it was deleted or mistyped.

To fix it, follow the first-time setup steps.

Tdarr Node keeps registering​

The Node uses a persistent outbound connection to the Server. If it keeps registering, check the Node and Server logs for connection errors, confirm both are running the same version, and make sure serverURL or serverIP points to a reachable Server. Firewalls and proxies must allow persistent Socket.IO traffic (WebSocket or HTTP polling) to port 8266 (or your configured serverPort). No inbound Node port is required.

Tdarr keeps crashing on Unraid​

Seems to be an issue with the Unraid cache/mover. Solution here.

I can't see the Tdarr UI in the browser, it just says Tdarr_Server​

Tdarr Server runs on port 8266, the UI runs on port 8265.

OpenEncodeSessionEx failed: out of memory​

If using an NVIDIA GPU, the card has most likely hit the stream limit.

Limits per GPU here.

CUDA_ERROR_NO_DEVICE: no CUDA-capable device​

https://github.com/HaveAGitGat/Tdarr/issues/666#issuecomment-1269275184

https://github.com/HaveAGitGat/Tdarr/issues/666#issuecomment-1368171781