def sample_create_model_deployment_monitoring_job(): # Create a client client = aiplatform_v1beta1.JobServiceClient() # Initialize request argument(s) model_deployment_monitoring_job = aiplatform_v1beta1.ModelDeploymentMonitoringJob() model_deployment_monitoring_job.display_name = "display_name_value" model_deployment_monitoring_job.endpoint = "endpoint_value" request = aiplatform_v1beta1.CreateModelDeploymentMonitoringJobRequest( parent="parent_value", model_deployment_monitoring_job=model_deployment_monitoring_job, ) # Make the request response = client.create_model_deployment_monitoring_job(request=request) # Handle the response print(response)
def sample_update_model_deployment_monitoring_job(): # Create a client client = aiplatform_v1beta1.JobServiceClient() # Initialize request argument(s) model_deployment_monitoring_job = aiplatform_v1beta1.ModelDeploymentMonitoringJob( ) model_deployment_monitoring_job.display_name = "display_name_value" model_deployment_monitoring_job.endpoint = "endpoint_value" request = aiplatform_v1beta1.UpdateModelDeploymentMonitoringJobRequest( model_deployment_monitoring_job=model_deployment_monitoring_job, ) # Make the request operation = client.update_model_deployment_monitoring_job(request=request) print("Waiting for operation to complete...") response = operation.result() # Handle the response print(response)