Create a VPC Endpoint

You can create an interface endpoint to connect to SageMaker AI MLflow. For instructions, see Creating an interface endpoint. Make sure that you create interface endpoints for all of the subnets in your VPC from which you want to connect to SageMaker AI MLflow.

When you create an interface endpoint, ensure that the security groups on your endpoint allow inbound and outbound access for HTTPS traffic. For more information, see Control access to services with VPC endpoints.

Note

In addition to creating an interface endpoint to connect to SageMaker AI MLflow, create an interface endpoint to connect to the Amazon SageMaker API. When users call CreatePresignedMlflowTrackingServerUrl to get the URL to connect to SageMaker AI MLflow, that call goes through the interface endpoint used to connect to the SageMaker API.

When you create the interface endpoint, specify aws.sagemaker.AWS Region.experiments as the service name. After you create the interface endpoint, enable private DNS for your endpoint. When you connect to SageMaker AI MLflow from within the VPC using the SageMaker Python SDK, you connect through the interface endpoint instead of the public internet.

Within the AWS Management Console, you can use the following procedure to create an endpoint.

To create an endpoint

1. Navigate to the Amazon Virtual Private Cloud console.

2. Navigate to Endpoints.

3. Choose Create endpoint.

4. (Optional) For Name (tag), specify a name for the endpoint.

5. In the search bar under Services, specify experiments.

6. Select the endponit that you're creating.

7. For VPC, specify the name of the VPC.

8. Choose Create endpoint.