# Configure and create an endpoint
<a name="clarify-online-explainability-create-endpoint"></a>

Create a new endpoint configuration to fit your model, and use this configuration to create the endpoint. You can use the model container validated in the [pre-check step ](https://docs.aws.amazon.com/sagemaker/latest/dg/clarify-online-explainability-precheck.html) to create an endpoint and enable the SageMaker Clarify online explainability feature.

Use the `sagemaker_client` object to create an endpoint using the [CreateEndpointConfig](https://docs.aws.amazon.com//sagemaker/latest/APIReference/API_CreateEndpointConfig.html) API. Set the member `ClarifyExplainerConfig` inside the `ExplainerConfig` parameter as follows:

```
sagemaker_client.create_endpoint_config(
    EndpointConfigName='name-of-your-endpoint-config',
    ExplainerConfig={
        'ClarifyExplainerConfig': {
            'EnableExplanations': '`true`',
            'InferenceConfig': {
                ...
            },
            'ShapConfig': {
                ...
            }
        },
    },
    ProductionVariants=[{
        'VariantName': 'AllTraffic',
        'ModelName': 'name-of-your-model',
        'InitialInstanceCount': 1,
        'InstanceType': 'ml.m5.xlarge',
    }]
     ...
)
sagemaker_client.create_endpoint(
    EndpointName='name-of-your-endpoint',
    EndpointConfigName='name-of-your-endpoint-config'
)
```

The first call to the `sagemaker_client` object creates a new endpoint configuration with the explainability feature enabled. The second call uses the endpoint configuration to launch the endpoint.

**Note**  
You can also host multiple models in one container behind a [SageMaker AI real-time inference multi-model endpoint](https://docs.aws.amazon.com/sagemaker/latest/dg/multi-model-endpoints.html) and configure online explainability with SageMaker Clarify.