Seldon Core is an open-source platform designed to deploy machine learning models on Kubernetes. It allows developers to manage, scale, and monitor machine learning models in production environments. By leveraging Kubernetes, Seldon Core provides a robust infrastructure for serving models with high availability and scalability.
When using Seldon Core, you might encounter an error related to an Invalid REST request format. This issue typically manifests when a REST API call to a deployed model returns an error, indicating that the request payload is not in the expected format.
Developers may see error messages such as:
400 Bad RequestInvalid input formatThe root cause of the Invalid REST request format error is often a mismatch between the request payload and the model's expected input schema. Each model deployed with Seldon Core has a defined input schema that specifies the format, data types, and structure of the input data it can process.
Input schemas are crucial for ensuring that the data sent to a model is correctly interpreted. These schemas can include specifications such as:
To resolve the Invalid REST request format error, follow these steps:
Begin by reviewing the input schema defined for your model. This information is typically available in the model's documentation or configuration files. Ensure you understand the expected data types and structure.
Modify your REST request payload to match the expected input schema. This may involve:
Before sending the request, validate it against the model's input schema. You can use tools like JSONLint to ensure your JSON payload is correctly formatted.
Once the payload is correctly formatted, test the request by sending it to the model's REST endpoint. Use tools like Postman or curl to verify that the request is processed successfully.
By understanding the model's input schema and ensuring your request payload matches it, you can resolve the Invalid REST request format error in Seldon Core. For more detailed guidance, refer to the Seldon Core documentation.
(Perfect for DevOps & SREs)
(Perfect for DevOps & SREs)
