Seldon Core is an open-source platform designed to deploy machine learning models on Kubernetes. It provides a robust framework for scaling, managing, and monitoring machine learning models in production environments. By leveraging Kubernetes, Seldon Core allows for seamless integration with existing cloud-native infrastructure, offering features such as canary deployments, A/B testing, and advanced metrics.
When interacting with a model endpoint deployed via Seldon Core, you might encounter authentication errors. These errors typically manifest as HTTP status codes like 401 Unauthorized
or 403 Forbidden
. Such errors indicate that the request to the model endpoint lacks proper authentication credentials or that the credentials provided are incorrect.
401 Unauthorized
error when attempting to access the model endpoint.403 Forbidden
error despite providing authentication details.The primary cause of authentication errors in Seldon Core is the absence or misconfiguration of authentication tokens or headers in the request. Seldon Core endpoints often require specific tokens or API keys to verify the identity of the client making the request. If these tokens are missing, expired, or incorrectly formatted, the server will reject the request.
Authorization
header in the HTTP request.To resolve authentication errors with Seldon Core model endpoints, follow these steps:
Authorization
header in your HTTP request. The format typically follows: Authorization: Bearer <your_token>
.kubectl logs <pod_name>
to view logs directly from the Kubernetes pods running your model.For more information on configuring authentication in Seldon Core, refer to the official Seldon Core documentation. Additionally, the Kubernetes documentation provides insights into managing secrets and configurations within a Kubernetes environment.
(Perfect for DevOps & SREs)
(Perfect for DevOps & SREs)