Cloud AI Platform v1beta1 API - Class ModelMonitor (1.0.0-beta02)

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

Reference documentation and code samples for the Cloud AI Platform v1beta1 API class ModelMonitor.

Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.

Inheritance

object > ModelMonitor

Namespace

Google.Cloud.AIPlatform.V1Beta1

Assembly

Google.Cloud.AIPlatform.V1Beta1.dll

Constructors

ModelMonitor()

public ModelMonitor()

ModelMonitor(ModelMonitor)

public ModelMonitor(ModelMonitor other)
Parameter
Name Description
other ModelMonitor

Properties

CreateTime

public Timestamp CreateTime { get; set; }

Output only. Timestamp when this ModelMonitor was created.

Property Value
Type Description
Timestamp

DefaultObjectiveCase

public ModelMonitor.DefaultObjectiveOneofCase DefaultObjectiveCase { get; }
Property Value
Type Description
ModelMonitorDefaultObjectiveOneofCase

DisplayName

public string DisplayName { get; set; }

The display name of the ModelMonitor. The name can be up to 128 characters long and can consist of any UTF-8.

Property Value
Type Description
string

ExplanationSpec

public ExplanationSpec ExplanationSpec { get; set; }

Optional model explanation spec. It is used for feature attribution monitoring.

Property Value
Type Description
ExplanationSpec

ModelMonitorName

public ModelMonitorName ModelMonitorName { get; set; }

ModelMonitorName-typed view over the Name resource name property.

Property Value
Type Description
ModelMonitorName

ModelMonitoringSchema

public ModelMonitoringSchema ModelMonitoringSchema { get; set; }

Monitoring Schema is to specify the model's features, prediction outputs and ground truth properties. It is used to extract pertinent data from the dataset and to process features based on their properties. Make sure that the schema aligns with your dataset, if it does not, we will be unable to extract data from the dataset. It is required for most models, but optional for Vertex AI AutoML Tables unless the schem information is not available.

Property Value
Type Description
ModelMonitoringSchema

ModelMonitoringTarget

public ModelMonitor.Types.ModelMonitoringTarget ModelMonitoringTarget { get; set; }

The entity that is subject to analysis. Currently only models in Vertex AI Model Registry are supported. If you want to analyze the model which is outside the Vertex AI, you could register a model in Vertex AI Model Registry using just a display name.

Property Value
Type Description
ModelMonitorTypesModelMonitoringTarget

Name

public string Name { get; set; }

Immutable. Resource name of the ModelMonitor. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor}.

Property Value
Type Description
string

NotificationSpec

public ModelMonitoringNotificationSpec NotificationSpec { get; set; }

Optional default notification spec, it can be overridden in the ModelMonitoringJob notification spec.

Property Value
Type Description
ModelMonitoringNotificationSpec

OutputSpec

public ModelMonitoringOutputSpec OutputSpec { get; set; }

Optional default monitoring metrics/logs export spec, it can be overridden in the ModelMonitoringJob output spec. If not specified, a default Google Cloud Storage bucket will be created under your project.

Property Value
Type Description
ModelMonitoringOutputSpec

SatisfiesPzi

public bool SatisfiesPzi { get; set; }

Output only. Reserved for future use.

Property Value
Type Description
bool

SatisfiesPzs

public bool SatisfiesPzs { get; set; }

Output only. Reserved for future use.

Property Value
Type Description
bool

TabularObjective

public ModelMonitoringObjectiveSpec.Types.TabularObjective TabularObjective { get; set; }

Optional default tabular model monitoring objective.

Property Value
Type Description
ModelMonitoringObjectiveSpecTypesTabularObjective

TrainingDataset

public ModelMonitoringInput TrainingDataset { get; set; }

Optional training dataset used to train the model. It can serve as a reference dataset to identify changes in production.

Property Value
Type Description
ModelMonitoringInput

UpdateTime

public Timestamp UpdateTime { get; set; }

Output only. Timestamp when this ModelMonitor was updated most recently.

Property Value
Type Description
Timestamp