Creating a Model Endpoint using API

You can select a specific Cloudera AI Inference service instance and a model version from Cloudera Model Registry to create a new model endpoint.

  1. Retrieve a registered model's model ID and model version.

    This information is available in the Registered Models page in the CML control plane UI.

  2. Create the model specification for the selected model.
    # cat ./examples/mlflow/model-spec-cml-registry.json
    {
      "namespace": "serving-default",
      "name": "mlflow-wine-test-from-registry-onnx",
      "source": {
        "registry_source": {
          "version": 2, 
          "model_id": "3azn-tmqe-wsze-5u4s"
        }
      }
    }
    
    export DOMAIN=$(cdp ml describe-ml-serving-app --app-crn [***app-crn***] | jq -r '.app.cluster.domainName')
  3. Create the model endpoint by using the following Cloudera Machine Learning serving deployEndpoint API:
    curl -v  -H "Content-Type: application/json" -H "Authorization: Bearer ${CDP_TOKEN}" "https://${DOMAIN}/api/v1alpha1/deployEndpoint" -d @./examples/mlflow/model-spec-cml-registry.json

    The DOMAIN looks like ml-67814ad5-b79.eng-ml-d.xcu2-8y8x.dev.cldr.work.

    You can retrieve the CDP_TOKEN by performing the steps from Preparing to interact with the Cloudera AI.