Seldon Core Model server port conflicts

Port already in use by another process or service.

Understanding Seldon Core

Seldon Core is an open-source platform designed to deploy machine learning models on Kubernetes. It allows data scientists and engineers to manage, scale, and monitor their models efficiently. By leveraging Kubernetes, Seldon Core provides a robust infrastructure for model serving, ensuring high availability and scalability.

Identifying the Symptom: Model Server Port Conflicts

When deploying models using Seldon Core, you might encounter a situation where the model server fails to start. The error message typically indicates a port conflict, suggesting that the specified port is already in use. This can prevent your model from being accessible and disrupt your deployment process.

Exploring the Issue: Port Already in Use

Port conflicts occur when multiple processes attempt to bind to the same network port. In the context of Seldon Core, this usually happens because the default port for the model server is already occupied by another service or process. This can be a common issue in environments where multiple applications are running simultaneously.

Common Error Message

The error message you might see in the logs could look like this:

Error: Port 9000 is already in use

This indicates that the port specified for the model server is not available, and the server cannot start.

Steps to Resolve Port Conflicts

Step 1: Identify the Conflicting Process

First, you need to identify which process is using the port. You can do this using the following command:

lsof -i :9000

This command will list the process ID (PID) and the application using the port.

Step 2: Choose an Available Port

Once you have identified the conflicting process, you can either stop it or choose a different port for your Seldon Core deployment. To find an available port, you can use:

netstat -tuln | grep LISTEN

This will list all the ports currently in use. Choose a port that is not listed.

Step 3: Update Seldon Core Configuration

After selecting an available port, update your Seldon Core deployment configuration. Modify the YAML file to specify the new port:

apiVersion: machinelearning.seldon.io/v1
kind: SeldonDeployment
metadata:
name: my-model
spec:
predictors:
- graph:
name: classifier
implementation: SKLEARN_SERVER
modelUri: gs://my-bucket/my-model
name: default
replicas: 1
annotations:
seldon.io/port: ""

Replace <new-port-number> with the port you have chosen.

Additional Resources

For more information on configuring Seldon Core, you can refer to the official Seldon Core Documentation. If you need further assistance, consider visiting the Seldon Core GitHub Issues page to see if others have encountered similar problems.

By following these steps, you should be able to resolve port conflicts and ensure your Seldon Core model server runs smoothly.

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