:doc:`MachineLearning <../../machinelearning>` / Client / create_realtime_endpoint

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create_realtime_endpoint
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.. py:method:: MachineLearning.Client.create_realtime_endpoint(**kwargs)

  

  Creates a real-time endpoint for the ``MLModel``. The endpoint contains the URI of the ``MLModel``; that is, the location to send real-time prediction requests for the specified ``MLModel``.

  

  See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/machinelearning-2014-12-12/CreateRealtimeEndpoint>`_  


  **Request Syntax**
  ::

    response = client.create_realtime_endpoint(
        MLModelId='string'
    )
    
  :type MLModelId: string
  :param MLModelId: **[REQUIRED]** 

    The ID assigned to the ``MLModel`` during creation.

    

  
  
  :rtype: dict
  :returns: 
    
    **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 ``CreateRealtimeEndpoint`` operation.

       

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

       

      **Note:** The endpoint information includes the URI of the ``MLModel``; that is, the location to send online prediction requests for the specified ``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.
          

          
    
  
  **Exceptions**
  
  *   :py:class:`MachineLearning.Client.exceptions.InvalidInputException`

  
  *   :py:class:`MachineLearning.Client.exceptions.ResourceNotFoundException`

  
  *   :py:class:`MachineLearning.Client.exceptions.InternalServerException`

  