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)