Google Cloud Native is in preview. Google Cloud Classic is fully supported.
google-native.aiplatform/v1.FeatureGroupFeature
Explore with Pulumi AI
Google Cloud Native is in preview. Google Cloud Classic is fully supported.
Creates a new Feature in a given FeatureGroup. Auto-naming is currently not supported for this resource.
Create FeatureGroupFeature Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new FeatureGroupFeature(name: string, args: FeatureGroupFeatureArgs, opts?: CustomResourceOptions);@overload
def FeatureGroupFeature(resource_name: str,
                        args: FeatureGroupFeatureArgs,
                        opts: Optional[ResourceOptions] = None)
@overload
def FeatureGroupFeature(resource_name: str,
                        opts: Optional[ResourceOptions] = None,
                        feature_group_id: Optional[str] = None,
                        feature_id: Optional[str] = None,
                        description: Optional[str] = None,
                        disable_monitoring: Optional[bool] = None,
                        etag: Optional[str] = None,
                        labels: Optional[Mapping[str, str]] = None,
                        location: Optional[str] = None,
                        name: Optional[str] = None,
                        project: Optional[str] = None,
                        value_type: Optional[FeatureGroupFeatureValueType] = None,
                        version_column_name: Optional[str] = None)func NewFeatureGroupFeature(ctx *Context, name string, args FeatureGroupFeatureArgs, opts ...ResourceOption) (*FeatureGroupFeature, error)public FeatureGroupFeature(string name, FeatureGroupFeatureArgs args, CustomResourceOptions? opts = null)
public FeatureGroupFeature(String name, FeatureGroupFeatureArgs args)
public FeatureGroupFeature(String name, FeatureGroupFeatureArgs args, CustomResourceOptions options)
type: google-native:aiplatform/v1:FeatureGroupFeature
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args FeatureGroupFeatureArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args FeatureGroupFeatureArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args FeatureGroupFeatureArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args FeatureGroupFeatureArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args FeatureGroupFeatureArgs
- 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 featureGroupFeatureResource = new GoogleNative.Aiplatform.V1.FeatureGroupFeature("featureGroupFeatureResource", new()
{
    FeatureGroupId = "string",
    FeatureId = "string",
    Description = "string",
    DisableMonitoring = false,
    Etag = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Location = "string",
    Name = "string",
    Project = "string",
    ValueType = GoogleNative.Aiplatform.V1.FeatureGroupFeatureValueType.ValueTypeUnspecified,
    VersionColumnName = "string",
});
example, err := aiplatform.NewFeatureGroupFeature(ctx, "featureGroupFeatureResource", &aiplatform.FeatureGroupFeatureArgs{
	FeatureGroupId:    pulumi.String("string"),
	FeatureId:         pulumi.String("string"),
	Description:       pulumi.String("string"),
	DisableMonitoring: pulumi.Bool(false),
	Etag:              pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Location:          pulumi.String("string"),
	Name:              pulumi.String("string"),
	Project:           pulumi.String("string"),
	ValueType:         aiplatform.FeatureGroupFeatureValueTypeValueTypeUnspecified,
	VersionColumnName: pulumi.String("string"),
})
var featureGroupFeatureResource = new FeatureGroupFeature("featureGroupFeatureResource", FeatureGroupFeatureArgs.builder()
    .featureGroupId("string")
    .featureId("string")
    .description("string")
    .disableMonitoring(false)
    .etag("string")
    .labels(Map.of("string", "string"))
    .location("string")
    .name("string")
    .project("string")
    .valueType("VALUE_TYPE_UNSPECIFIED")
    .versionColumnName("string")
    .build());
feature_group_feature_resource = google_native.aiplatform.v1.FeatureGroupFeature("featureGroupFeatureResource",
    feature_group_id="string",
    feature_id="string",
    description="string",
    disable_monitoring=False,
    etag="string",
    labels={
        "string": "string",
    },
    location="string",
    name="string",
    project="string",
    value_type=google_native.aiplatform.v1.FeatureGroupFeatureValueType.VALUE_TYPE_UNSPECIFIED,
    version_column_name="string")
const featureGroupFeatureResource = new google_native.aiplatform.v1.FeatureGroupFeature("featureGroupFeatureResource", {
    featureGroupId: "string",
    featureId: "string",
    description: "string",
    disableMonitoring: false,
    etag: "string",
    labels: {
        string: "string",
    },
    location: "string",
    name: "string",
    project: "string",
    valueType: google_native.aiplatform.v1.FeatureGroupFeatureValueType.ValueTypeUnspecified,
    versionColumnName: "string",
});
type: google-native:aiplatform/v1:FeatureGroupFeature
properties:
    description: string
    disableMonitoring: false
    etag: string
    featureGroupId: string
    featureId: string
    labels:
        string: string
    location: string
    name: string
    project: string
    valueType: VALUE_TYPE_UNSPECIFIED
    versionColumnName: string
FeatureGroupFeature 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 FeatureGroupFeature resource accepts the following input properties:
- FeatureGroup stringId 
- FeatureId string
- Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
- Description string
- Description of the Feature.
- DisableMonitoring bool
- Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- Etag string
- 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 Features. 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 Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- Location string
- Name string
- Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
- Project string
- ValueType Pulumi.Google Native. Aiplatform. V1. Feature Group Feature Value Type 
- Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- VersionColumn stringName 
- Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- FeatureGroup stringId 
- FeatureId string
- Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
- Description string
- Description of the Feature.
- DisableMonitoring bool
- Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- Etag string
- 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 Features. 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 Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- Location string
- Name string
- Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
- Project string
- ValueType FeatureGroup Feature Value Type 
- Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- VersionColumn stringName 
- Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- featureGroup StringId 
- featureId String
- Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
- description String
- Description of the Feature.
- disableMonitoring Boolean
- Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag String
- 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 Features. 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 Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location String
- name String
- Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
- project String
- valueType FeatureGroup Feature Value Type 
- Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- versionColumn StringName 
- Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- featureGroup stringId 
- featureId string
- Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
- description string
- Description of the Feature.
- disableMonitoring boolean
- Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag string
- 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 Features. 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 Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location string
- name string
- Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
- project string
- valueType FeatureGroup Feature Value Type 
- Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- versionColumn stringName 
- Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- feature_group_ strid 
- feature_id str
- Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
- description str
- Description of the Feature.
- disable_monitoring bool
- Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag str
- 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 Features. 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 Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location str
- name str
- Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
- project str
- value_type FeatureGroup Feature Value Type 
- Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- version_column_ strname 
- Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
- featureGroup StringId 
- featureId String
- Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup.
- description String
- Description of the Feature.
- disableMonitoring Boolean
- Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType.
- etag String
- 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 Features. 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 Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable.
- location String
- name String
- Immutable. Name of the Feature. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature}projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type.
- project String
- valueType "VALUE_TYPE_UNSPECIFIED" | "BOOL" | "BOOL_ARRAY" | "DOUBLE" | "DOUBLE_ARRAY" | "INT64" | "INT64_ARRAY" | "STRING" | "STRING_ARRAY" | "BYTES"
- Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
- versionColumn StringName 
- Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View columnn hosting data for this version. If no value is provided, will use feature_id.
Outputs
All input properties are implicitly available as output properties. Additionally, the FeatureGroupFeature resource produces the following output properties:
- CreateTime string
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- MonitoringStats List<Pulumi.Anomalies Google Native. Aiplatform. V1. Outputs. Google Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response> 
- Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- UpdateTime string
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- CreateTime string
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- Id string
- The provider-assigned unique ID for this managed resource.
- MonitoringStats []GoogleAnomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response 
- Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- UpdateTime string
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- createTime String
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id String
- The provider-assigned unique ID for this managed resource.
- monitoringStats List<GoogleAnomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response> 
- Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- updateTime String
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- createTime string
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id string
- The provider-assigned unique ID for this managed resource.
- monitoringStats GoogleAnomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response[] 
- Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- updateTime string
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- create_time str
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id str
- The provider-assigned unique ID for this managed resource.
- monitoring_stats_ Sequence[Googleanomalies Cloud Aiplatform V1Feature Monitoring Stats Anomaly Response] 
- Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- update_time str
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
- createTime String
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created.
- id String
- The provider-assigned unique ID for this managed resource.
- monitoringStats List<Property Map>Anomalies 
- Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives.
- updateTime String
- Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated.
Supporting Types
FeatureGroupFeatureValueType, FeatureGroupFeatureValueTypeArgs          
- ValueType Unspecified 
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Bool
- BOOLUsed for Feature that is a boolean.
- BoolArray 
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- Double
- DOUBLEUsed for Feature that is double.
- DoubleArray 
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- Int64
- INT64Used for Feature that is INT64.
- Int64Array
- INT64_ARRAYUsed for Feature that is a list of INT64.
- String
- STRINGUsed for Feature that is string.
- StringArray 
- STRING_ARRAYUsed for Feature that is a list of String.
- Bytes
- BYTESUsed for Feature that is bytes.
- FeatureGroup Feature Value Type Value Type Unspecified 
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- FeatureGroup Feature Value Type Bool 
- BOOLUsed for Feature that is a boolean.
- FeatureGroup Feature Value Type Bool Array 
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- FeatureGroup Feature Value Type Double 
- DOUBLEUsed for Feature that is double.
- FeatureGroup Feature Value Type Double Array 
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- FeatureGroup Feature Value Type Int64 
- INT64Used for Feature that is INT64.
- FeatureGroup Feature Value Type Int64Array 
- INT64_ARRAYUsed for Feature that is a list of INT64.
- FeatureGroup Feature Value Type String 
- STRINGUsed for Feature that is string.
- FeatureGroup Feature Value Type String Array 
- STRING_ARRAYUsed for Feature that is a list of String.
- FeatureGroup Feature Value Type Bytes 
- BYTESUsed for Feature that is bytes.
- ValueType Unspecified 
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Bool
- BOOLUsed for Feature that is a boolean.
- BoolArray 
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- Double
- DOUBLEUsed for Feature that is double.
- DoubleArray 
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- Int64
- INT64Used for Feature that is INT64.
- Int64Array
- INT64_ARRAYUsed for Feature that is a list of INT64.
- String
- STRINGUsed for Feature that is string.
- StringArray 
- STRING_ARRAYUsed for Feature that is a list of String.
- Bytes
- BYTESUsed for Feature that is bytes.
- ValueType Unspecified 
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- Bool
- BOOLUsed for Feature that is a boolean.
- BoolArray 
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- Double
- DOUBLEUsed for Feature that is double.
- DoubleArray 
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- Int64
- INT64Used for Feature that is INT64.
- Int64Array
- INT64_ARRAYUsed for Feature that is a list of INT64.
- String
- STRINGUsed for Feature that is string.
- StringArray 
- STRING_ARRAYUsed for Feature that is a list of String.
- Bytes
- BYTESUsed for Feature that is bytes.
- VALUE_TYPE_UNSPECIFIED
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- BOOL
- BOOLUsed for Feature that is a boolean.
- BOOL_ARRAY
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- DOUBLE
- DOUBLEUsed for Feature that is double.
- DOUBLE_ARRAY
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- INT64
- INT64Used for Feature that is INT64.
- INT64_ARRAY
- INT64_ARRAYUsed for Feature that is a list of INT64.
- STRING
- STRINGUsed for Feature that is string.
- STRING_ARRAY
- STRING_ARRAYUsed for Feature that is a list of String.
- BYTES
- BYTESUsed for Feature that is bytes.
- "VALUE_TYPE_UNSPECIFIED"
- VALUE_TYPE_UNSPECIFIEDThe value type is unspecified.
- "BOOL"
- BOOLUsed for Feature that is a boolean.
- "BOOL_ARRAY"
- BOOL_ARRAYUsed for Feature that is a list of boolean.
- "DOUBLE"
- DOUBLEUsed for Feature that is double.
- "DOUBLE_ARRAY"
- DOUBLE_ARRAYUsed for Feature that is a list of double.
- "INT64"
- INT64Used for Feature that is INT64.
- "INT64_ARRAY"
- INT64_ARRAYUsed for Feature that is a list of INT64.
- "STRING"
- STRINGUsed for Feature that is string.
- "STRING_ARRAY"
- STRING_ARRAYUsed for Feature that is a list of String.
- "BYTES"
- BYTESUsed for Feature that is bytes.
GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponse, GoogleCloudAiplatformV1FeatureMonitoringStatsAnomalyResponseArgs                
- FeatureStats Pulumi.Anomaly Google Native. Aiplatform. V1. Inputs. Google Cloud Aiplatform V1Feature Stats Anomaly Response 
- The stats and anomalies generated at specific timestamp.
- Objective string
- The objective for each stats.
- FeatureStats GoogleAnomaly Cloud Aiplatform V1Feature Stats Anomaly Response 
- The stats and anomalies generated at specific timestamp.
- Objective string
- The objective for each stats.
- featureStats GoogleAnomaly Cloud Aiplatform V1Feature Stats Anomaly Response 
- The stats and anomalies generated at specific timestamp.
- objective String
- The objective for each stats.
- featureStats GoogleAnomaly Cloud Aiplatform V1Feature Stats Anomaly Response 
- The stats and anomalies generated at specific timestamp.
- objective string
- The objective for each stats.
- feature_stats_ Googleanomaly Cloud Aiplatform V1Feature Stats Anomaly Response 
- The stats and anomalies generated at specific timestamp.
- objective str
- The objective for each stats.
- featureStats Property MapAnomaly 
- The stats and anomalies generated at specific timestamp.
- objective String
- The objective for each stats.
GoogleCloudAiplatformV1FeatureStatsAnomalyResponse, GoogleCloudAiplatformV1FeatureStatsAnomalyResponseArgs              
- AnomalyDetection doubleThreshold 
- This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- AnomalyUri string
- Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- DistributionDeviation double
- Deviation from the current stats to baseline stats. 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.
- EndTime string
- The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- Score double
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- StartTime string
- The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- StatsUri string
- Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- AnomalyDetection float64Threshold 
- This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- AnomalyUri string
- Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- DistributionDeviation float64
- Deviation from the current stats to baseline stats. 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.
- EndTime string
- The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- Score float64
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- StartTime string
- The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- StatsUri string
- Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomalyDetection DoubleThreshold 
- This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomalyUri String
- Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distributionDeviation Double
- Deviation from the current stats to baseline stats. 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.
- endTime String
- The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score Double
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- startTime String
- The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- statsUri String
- Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomalyDetection numberThreshold 
- This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomalyUri string
- Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distributionDeviation number
- Deviation from the current stats to baseline stats. 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.
- endTime string
- The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score number
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- startTime string
- The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- statsUri string
- Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomaly_detection_ floatthreshold 
- This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomaly_uri str
- Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distribution_deviation float
- Deviation from the current stats to baseline stats. 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.
- end_time str
- The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score float
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- start_time str
- The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- stats_uri str
- Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
- anomalyDetection NumberThreshold 
- This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value.
- anomalyUri String
- Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/v0/anomalies.proto).
- distributionDeviation Number
- Deviation from the current stats to baseline stats. 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.
- endTime String
- The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values).
- score Number
- Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT.
- startTime String
- The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval).
- statsUri String
- Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message tensorflow.metadata.v0.FeatureNameStatistics.
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.