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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.aiplatform/v1.EntityType

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

Creates a new EntityType in a given Featurestore.

Create EntityType Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new EntityType(name: string, args: EntityTypeArgs, opts?: CustomResourceOptions);
@overload
def EntityType(resource_name: str,
               args: EntityTypeArgs,
               opts: Optional[ResourceOptions] = None)

@overload
def EntityType(resource_name: str,
               opts: Optional[ResourceOptions] = None,
               entity_type_id: Optional[str] = None,
               featurestore_id: Optional[str] = None,
               description: Optional[str] = None,
               etag: Optional[str] = None,
               labels: Optional[Mapping[str, str]] = None,
               location: Optional[str] = None,
               monitoring_config: Optional[GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs] = None,
               name: Optional[str] = None,
               offline_storage_ttl_days: Optional[int] = None,
               project: Optional[str] = None)
func NewEntityType(ctx *Context, name string, args EntityTypeArgs, opts ...ResourceOption) (*EntityType, error)
public EntityType(string name, EntityTypeArgs args, CustomResourceOptions? opts = null)
public EntityType(String name, EntityTypeArgs args)
public EntityType(String name, EntityTypeArgs args, CustomResourceOptions options)

type: google-native:aiplatform/v1:EntityType
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name This property is required. string
The unique name of the resource.
args This property is required. EntityTypeArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
resource_name This property is required. str
The unique name of the resource.
args This property is required. EntityTypeArgs
The arguments to resource properties.
opts ResourceOptions
Bag of options to control resource's behavior.
ctx Context
Context object for the current deployment.
name This property is required. string
The unique name of the resource.
args This property is required. EntityTypeArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name This property is required. string
The unique name of the resource.
args This property is required. EntityTypeArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name This property is required. String
The unique name of the resource.
args This property is required. EntityTypeArgs
The arguments to resource properties.
options CustomResourceOptions
Bag of options to control resource's behavior.

Constructor example

The following reference example uses placeholder values for all input properties.

var entityTypeResource = new GoogleNative.Aiplatform.V1.EntityType("entityTypeResource", new()
{
    EntityTypeId = "string",
    FeaturestoreId = "string",
    Description = "string",
    Etag = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    MonitoringConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs
    {
        CategoricalThresholdConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs
        {
            Value = 0,
        },
        ImportFeaturesAnalysis = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs
        {
            AnomalyDetectionBaseline = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline.BaselineUnspecified,
            State = GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState.StateUnspecified,
        },
        NumericalThresholdConfig = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs
        {
            Value = 0,
        },
        SnapshotAnalysis = new GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs
        {
            Disabled = false,
            MonitoringIntervalDays = 0,
            StalenessDays = 0,
        },
    },
    Name = "string",
    OfflineStorageTtlDays = 0,
    Project = "string",
});
Copy
example, err := aiplatform.NewEntityType(ctx, "entityTypeResource", &aiplatform.EntityTypeArgs{
	EntityTypeId:   pulumi.String("string"),
	FeaturestoreId: pulumi.String("string"),
	Description:    pulumi.String("string"),
	Etag:           pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Location: pulumi.String("string"),
	MonitoringConfig: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs{
		CategoricalThresholdConfig: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs{
			Value: pulumi.Float64(0),
		},
		ImportFeaturesAnalysis: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs{
			AnomalyDetectionBaseline: aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineBaselineUnspecified,
			State:                    aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateStateUnspecified,
		},
		NumericalThresholdConfig: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs{
			Value: pulumi.Float64(0),
		},
		SnapshotAnalysis: &aiplatform.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs{
			Disabled:               pulumi.Bool(false),
			MonitoringIntervalDays: pulumi.Int(0),
			StalenessDays:          pulumi.Int(0),
		},
	},
	Name:                  pulumi.String("string"),
	OfflineStorageTtlDays: pulumi.Int(0),
	Project:               pulumi.String("string"),
})
Copy
var entityTypeResource = new EntityType("entityTypeResource", EntityTypeArgs.builder()
    .entityTypeId("string")
    .featurestoreId("string")
    .description("string")
    .etag("string")
    .labels(Map.of("string", "string"))
    .location("string")
    .monitoringConfig(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs.builder()
        .categoricalThresholdConfig(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs.builder()
            .value(0)
            .build())
        .importFeaturesAnalysis(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs.builder()
            .anomalyDetectionBaseline("BASELINE_UNSPECIFIED")
            .state("STATE_UNSPECIFIED")
            .build())
        .numericalThresholdConfig(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs.builder()
            .value(0)
            .build())
        .snapshotAnalysis(GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs.builder()
            .disabled(false)
            .monitoringIntervalDays(0)
            .stalenessDays(0)
            .build())
        .build())
    .name("string")
    .offlineStorageTtlDays(0)
    .project("string")
    .build());
Copy
entity_type_resource = google_native.aiplatform.v1.EntityType("entityTypeResource",
    entity_type_id="string",
    featurestore_id="string",
    description="string",
    etag="string",
    labels={
        "string": "string",
    },
    location="string",
    monitoring_config={
        "categorical_threshold_config": {
            "value": 0,
        },
        "import_features_analysis": {
            "anomaly_detection_baseline": google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline.BASELINE_UNSPECIFIED,
            "state": google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState.STATE_UNSPECIFIED,
        },
        "numerical_threshold_config": {
            "value": 0,
        },
        "snapshot_analysis": {
            "disabled": False,
            "monitoring_interval_days": 0,
            "staleness_days": 0,
        },
    },
    name="string",
    offline_storage_ttl_days=0,
    project="string")
Copy
const entityTypeResource = new google_native.aiplatform.v1.EntityType("entityTypeResource", {
    entityTypeId: "string",
    featurestoreId: "string",
    description: "string",
    etag: "string",
    labels: {
        string: "string",
    },
    location: "string",
    monitoringConfig: {
        categoricalThresholdConfig: {
            value: 0,
        },
        importFeaturesAnalysis: {
            anomalyDetectionBaseline: google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline.BaselineUnspecified,
            state: google_native.aiplatform.v1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState.StateUnspecified,
        },
        numericalThresholdConfig: {
            value: 0,
        },
        snapshotAnalysis: {
            disabled: false,
            monitoringIntervalDays: 0,
            stalenessDays: 0,
        },
    },
    name: "string",
    offlineStorageTtlDays: 0,
    project: "string",
});
Copy
type: google-native:aiplatform/v1:EntityType
properties:
    description: string
    entityTypeId: string
    etag: string
    featurestoreId: string
    labels:
        string: string
    location: string
    monitoringConfig:
        categoricalThresholdConfig:
            value: 0
        importFeaturesAnalysis:
            anomalyDetectionBaseline: BASELINE_UNSPECIFIED
            state: STATE_UNSPECIFIED
        numericalThresholdConfig:
            value: 0
        snapshotAnalysis:
            disabled: false
            monitoringIntervalDays: 0
            stalenessDays: 0
    name: string
    offlineStorageTtlDays: 0
    project: string
Copy

EntityType Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The EntityType resource accepts the following input properties:

EntityTypeId
This property is required.
Changes to this property will trigger replacement.
string
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
FeaturestoreId
This property is required.
Changes to this property will trigger replacement.
string
Description string
Optional. Description of the EntityType.
Etag string
Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
Labels Dictionary<string, string>
Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
Location Changes to this property will trigger replacement. string
MonitoringConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
Name string
Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
OfflineStorageTtlDays int
Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
Project Changes to this property will trigger replacement. string
EntityTypeId
This property is required.
Changes to this property will trigger replacement.
string
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
FeaturestoreId
This property is required.
Changes to this property will trigger replacement.
string
Description string
Optional. Description of the EntityType.
Etag string
Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
Labels map[string]string
Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
Location Changes to this property will trigger replacement. string
MonitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs
Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
Name string
Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
OfflineStorageTtlDays int
Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
Project Changes to this property will trigger replacement. string
entityTypeId
This property is required.
Changes to this property will trigger replacement.
String
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
featurestoreId
This property is required.
Changes to this property will trigger replacement.
String
description String
Optional. Description of the EntityType.
etag String
Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
labels Map<String,String>
Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
location Changes to this property will trigger replacement. String
monitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
name String
Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
offlineStorageTtlDays Integer
Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
project Changes to this property will trigger replacement. String
entityTypeId
This property is required.
Changes to this property will trigger replacement.
string
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
featurestoreId
This property is required.
Changes to this property will trigger replacement.
string
description string
Optional. Description of the EntityType.
etag string
Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
labels {[key: string]: string}
Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
location Changes to this property will trigger replacement. string
monitoringConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
name string
Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
offlineStorageTtlDays number
Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
project Changes to this property will trigger replacement. string
entity_type_id
This property is required.
Changes to this property will trigger replacement.
str
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
featurestore_id
This property is required.
Changes to this property will trigger replacement.
str
description str
Optional. Description of the EntityType.
etag str
Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
labels Mapping[str, str]
Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
location Changes to this property will trigger replacement. str
monitoring_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs
Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
name str
Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
offline_storage_ttl_days int
Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
project Changes to this property will trigger replacement. str
entityTypeId
This property is required.
Changes to this property will trigger replacement.
String
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within a featurestore.
featurestoreId
This property is required.
Changes to this property will trigger replacement.
String
description String
Optional. Description of the EntityType.
etag String
Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
labels Map<String>
Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
location Changes to this property will trigger replacement. String
monitoringConfig Property Map
Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled.
name String
Immutable. Name of the EntityType. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore.
offlineStorageTtlDays Number
Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than offline_storage_ttl_days since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL.
project Changes to this property will trigger replacement. String

Outputs

All input properties are implicitly available as output properties. Additionally, the EntityType resource produces the following output properties:

CreateTime string
Timestamp when this EntityType was created.
Id string
The provider-assigned unique ID for this managed resource.
UpdateTime string
Timestamp when this EntityType was most recently updated.
CreateTime string
Timestamp when this EntityType was created.
Id string
The provider-assigned unique ID for this managed resource.
UpdateTime string
Timestamp when this EntityType was most recently updated.
createTime String
Timestamp when this EntityType was created.
id String
The provider-assigned unique ID for this managed resource.
updateTime String
Timestamp when this EntityType was most recently updated.
createTime string
Timestamp when this EntityType was created.
id string
The provider-assigned unique ID for this managed resource.
updateTime string
Timestamp when this EntityType was most recently updated.
create_time str
Timestamp when this EntityType was created.
id str
The provider-assigned unique ID for this managed resource.
update_time str
Timestamp when this EntityType was most recently updated.
createTime String
Timestamp when this EntityType was created.
id String
The provider-assigned unique ID for this managed resource.
updateTime String
Timestamp when this EntityType was most recently updated.

Supporting Types

GoogleCloudAiplatformV1FeaturestoreMonitoringConfig
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigArgs

CategoricalThresholdConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
ImportFeaturesAnalysis Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
The config for ImportFeatures Analysis Based Feature Monitoring.
NumericalThresholdConfig Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
SnapshotAnalysis Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
The config for Snapshot Analysis Based Feature Monitoring.
CategoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
ImportFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
The config for ImportFeatures Analysis Based Feature Monitoring.
NumericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
SnapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
The config for Snapshot Analysis Based Feature Monitoring.
categoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
importFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
The config for ImportFeatures Analysis Based Feature Monitoring.
numericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
The config for Snapshot Analysis Based Feature Monitoring.
categoricalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
importFeaturesAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
The config for ImportFeatures Analysis Based Feature Monitoring.
numericalThresholdConfig GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshotAnalysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
The config for Snapshot Analysis Based Feature Monitoring.
categorical_threshold_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
import_features_analysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
The config for ImportFeatures Analysis Based Feature Monitoring.
numerical_threshold_config GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshot_analysis GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
The config for Snapshot Analysis Based Feature Monitoring.
categoricalThresholdConfig Property Map
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
importFeaturesAnalysis Property Map
The config for ImportFeatures Analysis Based Feature Monitoring.
numericalThresholdConfig Property Map
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshotAnalysis Property Map
The config for Snapshot Analysis Based Feature Monitoring.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysis
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisArgs

AnomalyDetectionBaseline Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
The baseline used to do anomaly detection for the statistics generated by import features analysis.
State Pulumi.GoogleNative.Aiplatform.V1.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
Whether to enable / disable / inherite default hebavior for import features analysis.
AnomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
The baseline used to do anomaly detection for the statistics generated by import features analysis.
State GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
Whether to enable / disable / inherite default hebavior for import features analysis.
anomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
Whether to enable / disable / inherite default hebavior for import features analysis.
anomalyDetectionBaseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
Whether to enable / disable / inherite default hebavior for import features analysis.
anomaly_detection_baseline GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
Whether to enable / disable / inherite default hebavior for import features analysis.
anomalyDetectionBaseline "BASELINE_UNSPECIFIED" | "LATEST_STATS" | "MOST_RECENT_SNAPSHOT_STATS" | "PREVIOUS_IMPORT_FEATURES_STATS"
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state "STATE_UNSPECIFIED" | "DEFAULT" | "ENABLED" | "DISABLED"
Whether to enable / disable / inherite default hebavior for import features analysis.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaseline
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineArgs

BaselineUnspecified
BASELINE_UNSPECIFIEDShould not be used.
LatestStats
LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
MostRecentSnapshotStats
MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
PreviousImportFeaturesStats
PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineBaselineUnspecified
BASELINE_UNSPECIFIEDShould not be used.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineLatestStats
LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselineMostRecentSnapshotStats
MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisAnomalyDetectionBaselinePreviousImportFeaturesStats
PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
BaselineUnspecified
BASELINE_UNSPECIFIEDShould not be used.
LatestStats
LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
MostRecentSnapshotStats
MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
PreviousImportFeaturesStats
PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
BaselineUnspecified
BASELINE_UNSPECIFIEDShould not be used.
LatestStats
LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
MostRecentSnapshotStats
MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
PreviousImportFeaturesStats
PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
BASELINE_UNSPECIFIED
BASELINE_UNSPECIFIEDShould not be used.
LATEST_STATS
LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
MOST_RECENT_SNAPSHOT_STATS
MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
PREVIOUS_IMPORT_FEATURES_STATS
PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.
"BASELINE_UNSPECIFIED"
BASELINE_UNSPECIFIEDShould not be used.
"LATEST_STATS"
LATEST_STATSChoose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics.
"MOST_RECENT_SNAPSHOT_STATS"
MOST_RECENT_SNAPSHOT_STATSUse the statistics generated by the most recent snapshot analysis if exists.
"PREVIOUS_IMPORT_FEATURES_STATS"
PREVIOUS_IMPORT_FEATURES_STATSUse the statistics generated by the previous import features analysis if exists.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponseArgs

AnomalyDetectionBaseline This property is required. string
The baseline used to do anomaly detection for the statistics generated by import features analysis.
State This property is required. string
Whether to enable / disable / inherite default hebavior for import features analysis.
AnomalyDetectionBaseline This property is required. string
The baseline used to do anomaly detection for the statistics generated by import features analysis.
State This property is required. string
Whether to enable / disable / inherite default hebavior for import features analysis.
anomalyDetectionBaseline This property is required. String
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state This property is required. String
Whether to enable / disable / inherite default hebavior for import features analysis.
anomalyDetectionBaseline This property is required. string
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state This property is required. string
Whether to enable / disable / inherite default hebavior for import features analysis.
anomaly_detection_baseline This property is required. str
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state This property is required. str
Whether to enable / disable / inherite default hebavior for import features analysis.
anomalyDetectionBaseline This property is required. String
The baseline used to do anomaly detection for the statistics generated by import features analysis.
state This property is required. String
Whether to enable / disable / inherite default hebavior for import features analysis.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisState
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateArgs

StateUnspecified
STATE_UNSPECIFIEDShould not be used.
Default
DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
Enabled
ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
Disabled
DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateStateUnspecified
STATE_UNSPECIFIEDShould not be used.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateDefault
DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateEnabled
ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisStateDisabled
DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
StateUnspecified
STATE_UNSPECIFIEDShould not be used.
Default
DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
Enabled
ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
Disabled
DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
StateUnspecified
STATE_UNSPECIFIEDShould not be used.
Default
DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
Enabled
ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
Disabled
DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
STATE_UNSPECIFIED
STATE_UNSPECIFIEDShould not be used.
DEFAULT
DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
ENABLED
ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
DISABLED
DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.
"STATE_UNSPECIFIED"
STATE_UNSPECIFIEDShould not be used.
"DEFAULT"
DEFAULTThe default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to.
"ENABLED"
ENABLEDExplicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config.
"DISABLED"
DISABLEDExplicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponse
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigResponseArgs

CategoricalThresholdConfig This property is required. Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
ImportFeaturesAnalysis This property is required. Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
The config for ImportFeatures Analysis Based Feature Monitoring.
NumericalThresholdConfig This property is required. Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
SnapshotAnalysis This property is required. Pulumi.GoogleNative.Aiplatform.V1.Inputs.GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
The config for Snapshot Analysis Based Feature Monitoring.
CategoricalThresholdConfig This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
ImportFeaturesAnalysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
The config for ImportFeatures Analysis Based Feature Monitoring.
NumericalThresholdConfig This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
SnapshotAnalysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
The config for Snapshot Analysis Based Feature Monitoring.
categoricalThresholdConfig This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
importFeaturesAnalysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
The config for ImportFeatures Analysis Based Feature Monitoring.
numericalThresholdConfig This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshotAnalysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
The config for Snapshot Analysis Based Feature Monitoring.
categoricalThresholdConfig This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
importFeaturesAnalysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
The config for ImportFeatures Analysis Based Feature Monitoring.
numericalThresholdConfig This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshotAnalysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
The config for Snapshot Analysis Based Feature Monitoring.
categorical_threshold_config This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
import_features_analysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigImportFeaturesAnalysisResponse
The config for ImportFeatures Analysis Based Feature Monitoring.
numerical_threshold_config This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshot_analysis This property is required. GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
The config for Snapshot Analysis Based Feature Monitoring.
categoricalThresholdConfig This property is required. Property Map
Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING).
importFeaturesAnalysis This property is required. Property Map
The config for ImportFeatures Analysis Based Feature Monitoring.
numericalThresholdConfig This property is required. Property Map
Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64).
snapshotAnalysis This property is required. Property Map
The config for Snapshot Analysis Based Feature Monitoring.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysis
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisArgs

Disabled bool
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
MonitoringIntervalDays int
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
StalenessDays int
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
Disabled bool
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
MonitoringIntervalDays int
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
StalenessDays int
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled Boolean
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoringIntervalDays Integer
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays Integer
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled boolean
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoringIntervalDays number
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays number
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled bool
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoring_interval_days int
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
staleness_days int
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled Boolean
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoringIntervalDays Number
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays Number
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponse
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigSnapshotAnalysisResponseArgs

Disabled This property is required. bool
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
MonitoringIntervalDays This property is required. int
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
StalenessDays This property is required. int
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
Disabled This property is required. bool
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
MonitoringIntervalDays This property is required. int
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
StalenessDays This property is required. int
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled This property is required. Boolean
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoringIntervalDays This property is required. Integer
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays This property is required. Integer
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled This property is required. boolean
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoringIntervalDays This property is required. number
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays This property is required. number
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled This property is required. bool
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoring_interval_days This property is required. int
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
staleness_days This property is required. int
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.
disabled This property is required. Boolean
The monitoring schedule for snapshot analysis. For EntityType-level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType-level config; unset monitoring_interval indicates going with EntityType-level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring.
monitoringIntervalDays This property is required. Number
Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days.
stalenessDays This property is required. Number
Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfig
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigArgs

Value double
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
Value float64
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value Double
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value number
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value float
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value Number
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponse
, GoogleCloudAiplatformV1FeaturestoreMonitoringConfigThresholdConfigResponseArgs

Value This property is required. double
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
Value This property is required. float64
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value This property is required. Double
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value This property is required. number
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value This property is required. float
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
value This property is required. Number
Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.

Package Details

Repository
Google Cloud Native pulumi/pulumi-google-native
License
Apache-2.0

Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native