Deletes a real time endpoint of an MLModel .

See also: AWS API Documentation

Request Syntax

response = client.delete_realtime_endpoint(
MLModelId (string) --


The ID assigned to the MLModel during creation.

Return type
Response Syntax
    'MLModelId': 'string',
    'RealtimeEndpointInfo': {
        'PeakRequestsPerSecond': 123,
        'CreatedAt': datetime(2015, 1, 1),
        'EndpointUrl': 'string',
        'EndpointStatus': 'NONE'|'READY'|'UPDATING'|'FAILED'

Response Structure

  • (dict) --

    Represents the output of an DeleteRealtimeEndpoint operation.

    The result contains the MLModelId and the endpoint information for the MLModel .

    • MLModelId (string) --

      A user-supplied ID that uniquely identifies the MLModel . This value should be identical to the value of the MLModelId in the request.

    • RealtimeEndpointInfo (dict) --

      The endpoint information of the MLModel

      • PeakRequestsPerSecond (integer) --

        The maximum processing rate for the real-time endpoint for MLModel , measured in incoming requests per second.

      • CreatedAt (datetime) --

        The time that the request to create the real-time endpoint for the MLModel was received. The time is expressed in epoch time.

      • EndpointUrl (string) --

        The URI that specifies where to send real-time prediction requests for the MLModel .

        Note: The application must wait until the real-time endpoint is ready before using this URI.
      • EndpointStatus (string) --

        The current status of the real-time endpoint for the MLModel . This element can have one of the following values:

        • NONE - Endpoint does not exist or was previously deleted.
        • READY - Endpoint is ready to be used for real-time predictions.
        • UPDATING - Updating/creating the endpoint.


  • MachineLearning.Client.exceptions.InvalidInputException
  • MachineLearning.Client.exceptions.ResourceNotFoundException
  • MachineLearning.Client.exceptions.InternalServerException