Vertex AI v1beta1 API - Class UpdateModelDeploymentMonitoringJobRequest (1.0.0-beta55) 

public sealed class UpdateModelDeploymentMonitoringJobRequest : IMessage<UpdateModelDeploymentMonitoringJobRequest>, IEquatable<UpdateModelDeploymentMonitoringJobRequest>, IDeepCloneable<UpdateModelDeploymentMonitoringJobRequest>, IBufferMessage, IMessage

Reference documentation and code samples for the Vertex AI v1beta1 API class UpdateModelDeploymentMonitoringJobRequest.

Request message for [JobService.UpdateModelDeploymentMonitoringJob][google.cloud.aiplatform.v1beta1.JobService.UpdateModelDeploymentMonitoringJob].

Inheritance

object > UpdateModelDeploymentMonitoringJobRequest

Namespace

Google.Cloud.AIPlatform.V1Beta1

Assembly

Google.Cloud.AIPlatform.V1Beta1.dll

Constructors

UpdateModelDeploymentMonitoringJobRequest()

public UpdateModelDeploymentMonitoringJobRequest()

UpdateModelDeploymentMonitoringJobRequest(UpdateModelDeploymentMonitoringJobRequest)

public UpdateModelDeploymentMonitoringJobRequest(UpdateModelDeploymentMonitoringJobRequest other)
Parameter
Name Description
other UpdateModelDeploymentMonitoringJobRequest

Properties

ModelDeploymentMonitoringJob

public ModelDeploymentMonitoringJob ModelDeploymentMonitoringJob { get; set; }

Required. The model monitoring configuration which replaces the resource on the server.

Property Value
Type Description
ModelDeploymentMonitoringJob

UpdateMask

public FieldMask UpdateMask { get; set; }

Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.objective_config.training_dataset.

Updatable fields:

  • display_name
  • model_deployment_monitoring_schedule_config
  • model_monitoring_alert_config
  • logging_sampling_strategy
  • labels
  • log_ttl
  • enable_monitoring_pipeline_logs . and
  • model_deployment_monitoring_objective_configs . or
  • model_deployment_monitoring_objective_configs.objective_config.training_dataset
  • model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config
  • model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config
Property Value
Type Description
FieldMask