MachineLearning / Client / delete_realtime_endpoint
delete_realtime_endpoint#
- MachineLearning.Client.delete_realtime_endpoint(**kwargs)#
Deletes a real time endpoint of an
MLModel
.See also: AWS API Documentation
Request Syntax
response = client.delete_realtime_endpoint( MLModelId='string' )
- Parameters:
MLModelId (string) –
[REQUIRED]
The ID assigned to the
MLModel
during creation.- Return type:
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
DeleteRealtimeEndpoint
operation.The result contains the
MLModelId
and the endpoint information for theMLModel
.MLModelId (string) –
A user-supplied ID that uniquely identifies the
MLModel
. This value should be identical to the value of theMLModelId
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