gcp.vertex.AiFeatureStoreEntityTypeFeature

Feature Metadata information that describes an attribute of an entity type. For example, apple is an entity type, and color is a feature that describes apple.

To get more information about FeaturestoreEntitytypeFeature, see:

Example Usage

Vertex Ai Featurestore Entitytype Feature

using System.Collections.Generic;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var featurestore = new Gcp.Vertex.AiFeatureStore("featurestore", new()
    {
        Labels = 
        {
            { "foo", "bar" },
        },
        Region = "us-central1",
        OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
        {
            FixedNodeCount = 2,
        },
    });

    var entity = new Gcp.Vertex.AiFeatureStoreEntityType("entity", new()
    {
        Labels = 
        {
            { "foo", "bar" },
        },
        Featurestore = featurestore.Id,
    });

    var feature = new Gcp.Vertex.AiFeatureStoreEntityTypeFeature("feature", new()
    {
        Labels = 
        {
            { "foo", "bar" },
        },
        Entitytype = entity.Id,
        ValueType = "INT64_ARRAY",
    });

});
package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v6/go/gcp/vertex"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		featurestore, err := vertex.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			Region: pulumi.String("us-central1"),
			OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
				FixedNodeCount: pulumi.Int(2),
			},
		})
		if err != nil {
			return err
		}
		entity, err := vertex.NewAiFeatureStoreEntityType(ctx, "entity", &vertex.AiFeatureStoreEntityTypeArgs{
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			Featurestore: featurestore.ID(),
		})
		if err != nil {
			return err
		}
		_, err = vertex.NewAiFeatureStoreEntityTypeFeature(ctx, "feature", &vertex.AiFeatureStoreEntityTypeFeatureArgs{
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			Entitytype: entity.ID(),
			ValueType:  pulumi.String("INT64_ARRAY"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}
package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityType;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeArgs;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeFeature;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeFeatureArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()        
            .labels(Map.of("foo", "bar"))
            .region("us-central1")
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .fixedNodeCount(2)
                .build())
            .build());

        var entity = new AiFeatureStoreEntityType("entity", AiFeatureStoreEntityTypeArgs.builder()        
            .labels(Map.of("foo", "bar"))
            .featurestore(featurestore.id())
            .build());

        var feature = new AiFeatureStoreEntityTypeFeature("feature", AiFeatureStoreEntityTypeFeatureArgs.builder()        
            .labels(Map.of("foo", "bar"))
            .entitytype(entity.id())
            .valueType("INT64_ARRAY")
            .build());

    }
}
import pulumi
import pulumi_gcp as gcp

featurestore = gcp.vertex.AiFeatureStore("featurestore",
    labels={
        "foo": "bar",
    },
    region="us-central1",
    online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
        fixed_node_count=2,
    ))
entity = gcp.vertex.AiFeatureStoreEntityType("entity",
    labels={
        "foo": "bar",
    },
    featurestore=featurestore.id)
feature = gcp.vertex.AiFeatureStoreEntityTypeFeature("feature",
    labels={
        "foo": "bar",
    },
    entitytype=entity.id,
    value_type="INT64_ARRAY")
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
    labels: {
        foo: "bar",
    },
    region: "us-central1",
    onlineServingConfig: {
        fixedNodeCount: 2,
    },
});
const entity = new gcp.vertex.AiFeatureStoreEntityType("entity", {
    labels: {
        foo: "bar",
    },
    featurestore: featurestore.id,
});
const feature = new gcp.vertex.AiFeatureStoreEntityTypeFeature("feature", {
    labels: {
        foo: "bar",
    },
    entitytype: entity.id,
    valueType: "INT64_ARRAY",
});
resources:
  featurestore:
    type: gcp:vertex:AiFeatureStore
    properties:
      labels:
        foo: bar
      region: us-central1
      onlineServingConfig:
        fixedNodeCount: 2
  entity:
    type: gcp:vertex:AiFeatureStoreEntityType
    properties:
      labels:
        foo: bar
      featurestore: ${featurestore.id}
  feature:
    type: gcp:vertex:AiFeatureStoreEntityTypeFeature
    properties:
      labels:
        foo: bar
      entitytype: ${entity.id}
      valueType: INT64_ARRAY

Vertex Ai Featurestore Entitytype Feature With Beta Fields

using System.Collections.Generic;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var featurestore = new Gcp.Vertex.AiFeatureStore("featurestore", new()
    {
        Labels = 
        {
            { "foo", "bar" },
        },
        Region = "us-central1",
        OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
        {
            FixedNodeCount = 2,
        },
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

    var entity = new Gcp.Vertex.AiFeatureStoreEntityType("entity", new()
    {
        Labels = 
        {
            { "foo", "bar" },
        },
        Featurestore = featurestore.Id,
        MonitoringConfig = new Gcp.Vertex.Inputs.AiFeatureStoreEntityTypeMonitoringConfigArgs
        {
            SnapshotAnalysis = new Gcp.Vertex.Inputs.AiFeatureStoreEntityTypeMonitoringConfigSnapshotAnalysisArgs
            {
                Disabled = false,
                MonitoringInterval = "86400s",
            },
            CategoricalThresholdConfig = new Gcp.Vertex.Inputs.AiFeatureStoreEntityTypeMonitoringConfigCategoricalThresholdConfigArgs
            {
                Value = 0.3,
            },
            NumericalThresholdConfig = new Gcp.Vertex.Inputs.AiFeatureStoreEntityTypeMonitoringConfigNumericalThresholdConfigArgs
            {
                Value = 0.3,
            },
        },
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

    var feature = new Gcp.Vertex.AiFeatureStoreEntityTypeFeature("feature", new()
    {
        Labels = 
        {
            { "foo", "bar" },
        },
        Entitytype = entity.Id,
        ValueType = "INT64_ARRAY",
    }, new CustomResourceOptions
    {
        Provider = google_beta,
    });

});
package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v6/go/gcp/vertex"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		featurestore, err := vertex.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			Region: pulumi.String("us-central1"),
			OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
				FixedNodeCount: pulumi.Int(2),
			},
		}, pulumi.Provider(google_beta))
		if err != nil {
			return err
		}
		entity, err := vertex.NewAiFeatureStoreEntityType(ctx, "entity", &vertex.AiFeatureStoreEntityTypeArgs{
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			Featurestore: featurestore.ID(),
			MonitoringConfig: &vertex.AiFeatureStoreEntityTypeMonitoringConfigArgs{
				SnapshotAnalysis: &vertex.AiFeatureStoreEntityTypeMonitoringConfigSnapshotAnalysisArgs{
					Disabled:           pulumi.Bool(false),
					MonitoringInterval: pulumi.String("86400s"),
				},
				CategoricalThresholdConfig: &vertex.AiFeatureStoreEntityTypeMonitoringConfigCategoricalThresholdConfigArgs{
					Value: pulumi.Float64(0.3),
				},
				NumericalThresholdConfig: &vertex.AiFeatureStoreEntityTypeMonitoringConfigNumericalThresholdConfigArgs{
					Value: pulumi.Float64(0.3),
				},
			},
		}, pulumi.Provider(google_beta))
		if err != nil {
			return err
		}
		_, err = vertex.NewAiFeatureStoreEntityTypeFeature(ctx, "feature", &vertex.AiFeatureStoreEntityTypeFeatureArgs{
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			Entitytype: entity.ID(),
			ValueType:  pulumi.String("INT64_ARRAY"),
		}, pulumi.Provider(google_beta))
		if err != nil {
			return err
		}
		return nil
	})
}
package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityType;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEntityTypeMonitoringConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEntityTypeMonitoringConfigSnapshotAnalysisArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEntityTypeMonitoringConfigCategoricalThresholdConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEntityTypeMonitoringConfigNumericalThresholdConfigArgs;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeFeature;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeFeatureArgs;
import com.pulumi.resources.CustomResourceOptions;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()        
            .labels(Map.of("foo", "bar"))
            .region("us-central1")
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .fixedNodeCount(2)
                .build())
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());

        var entity = new AiFeatureStoreEntityType("entity", AiFeatureStoreEntityTypeArgs.builder()        
            .labels(Map.of("foo", "bar"))
            .featurestore(featurestore.id())
            .monitoringConfig(AiFeatureStoreEntityTypeMonitoringConfigArgs.builder()
                .snapshotAnalysis(AiFeatureStoreEntityTypeMonitoringConfigSnapshotAnalysisArgs.builder()
                    .disabled(false)
                    .monitoringInterval("86400s")
                    .build())
                .categoricalThresholdConfig(AiFeatureStoreEntityTypeMonitoringConfigCategoricalThresholdConfigArgs.builder()
                    .value(0.3)
                    .build())
                .numericalThresholdConfig(AiFeatureStoreEntityTypeMonitoringConfigNumericalThresholdConfigArgs.builder()
                    .value(0.3)
                    .build())
                .build())
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());

        var feature = new AiFeatureStoreEntityTypeFeature("feature", AiFeatureStoreEntityTypeFeatureArgs.builder()        
            .labels(Map.of("foo", "bar"))
            .entitytype(entity.id())
            .valueType("INT64_ARRAY")
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());

    }
}
import pulumi
import pulumi_gcp as gcp

featurestore = gcp.vertex.AiFeatureStore("featurestore",
    labels={
        "foo": "bar",
    },
    region="us-central1",
    online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
        fixed_node_count=2,
    ),
    opts=pulumi.ResourceOptions(provider=google_beta))
entity = gcp.vertex.AiFeatureStoreEntityType("entity",
    labels={
        "foo": "bar",
    },
    featurestore=featurestore.id,
    monitoring_config=gcp.vertex.AiFeatureStoreEntityTypeMonitoringConfigArgs(
        snapshot_analysis=gcp.vertex.AiFeatureStoreEntityTypeMonitoringConfigSnapshotAnalysisArgs(
            disabled=False,
            monitoring_interval="86400s",
        ),
        categorical_threshold_config=gcp.vertex.AiFeatureStoreEntityTypeMonitoringConfigCategoricalThresholdConfigArgs(
            value=0.3,
        ),
        numerical_threshold_config=gcp.vertex.AiFeatureStoreEntityTypeMonitoringConfigNumericalThresholdConfigArgs(
            value=0.3,
        ),
    ),
    opts=pulumi.ResourceOptions(provider=google_beta))
feature = gcp.vertex.AiFeatureStoreEntityTypeFeature("feature",
    labels={
        "foo": "bar",
    },
    entitytype=entity.id,
    value_type="INT64_ARRAY",
    opts=pulumi.ResourceOptions(provider=google_beta))
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
    labels: {
        foo: "bar",
    },
    region: "us-central1",
    onlineServingConfig: {
        fixedNodeCount: 2,
    },
}, {
    provider: google_beta,
});
const entity = new gcp.vertex.AiFeatureStoreEntityType("entity", {
    labels: {
        foo: "bar",
    },
    featurestore: featurestore.id,
    monitoringConfig: {
        snapshotAnalysis: {
            disabled: false,
            monitoringInterval: "86400s",
        },
        categoricalThresholdConfig: {
            value: 0.3,
        },
        numericalThresholdConfig: {
            value: 0.3,
        },
    },
}, {
    provider: google_beta,
});
const feature = new gcp.vertex.AiFeatureStoreEntityTypeFeature("feature", {
    labels: {
        foo: "bar",
    },
    entitytype: entity.id,
    valueType: "INT64_ARRAY",
}, {
    provider: google_beta,
});
resources:
  featurestore:
    type: gcp:vertex:AiFeatureStore
    properties:
      labels:
        foo: bar
      region: us-central1
      onlineServingConfig:
        fixedNodeCount: 2
    options:
      provider: ${["google-beta"]}
  entity:
    type: gcp:vertex:AiFeatureStoreEntityType
    properties:
      labels:
        foo: bar
      featurestore: ${featurestore.id}
      monitoringConfig:
        snapshotAnalysis:
          disabled: false
          monitoringInterval: 86400s
        categoricalThresholdConfig:
          value: 0.3
        numericalThresholdConfig:
          value: 0.3
    options:
      provider: ${["google-beta"]}
  feature:
    type: gcp:vertex:AiFeatureStoreEntityTypeFeature
    properties:
      labels:
        foo: bar
      entitytype: ${entity.id}
      valueType: INT64_ARRAY
    options:
      provider: ${["google-beta"]}

Create AiFeatureStoreEntityTypeFeature Resource

new AiFeatureStoreEntityTypeFeature(name: string, args: AiFeatureStoreEntityTypeFeatureArgs, opts?: CustomResourceOptions);
@overload
def AiFeatureStoreEntityTypeFeature(resource_name: str,
                                    opts: Optional[ResourceOptions] = None,
                                    description: Optional[str] = None,
                                    entitytype: Optional[str] = None,
                                    labels: Optional[Mapping[str, str]] = None,
                                    name: Optional[str] = None,
                                    value_type: Optional[str] = None)
@overload
def AiFeatureStoreEntityTypeFeature(resource_name: str,
                                    args: AiFeatureStoreEntityTypeFeatureArgs,
                                    opts: Optional[ResourceOptions] = None)
func NewAiFeatureStoreEntityTypeFeature(ctx *Context, name string, args AiFeatureStoreEntityTypeFeatureArgs, opts ...ResourceOption) (*AiFeatureStoreEntityTypeFeature, error)
public AiFeatureStoreEntityTypeFeature(string name, AiFeatureStoreEntityTypeFeatureArgs args, CustomResourceOptions? opts = null)
public AiFeatureStoreEntityTypeFeature(String name, AiFeatureStoreEntityTypeFeatureArgs args)
public AiFeatureStoreEntityTypeFeature(String name, AiFeatureStoreEntityTypeFeatureArgs args, CustomResourceOptions options)
type: gcp:vertex:AiFeatureStoreEntityTypeFeature
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

name string
The unique name of the resource.
args AiFeatureStoreEntityTypeFeatureArgs
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 AiFeatureStoreEntityTypeFeatureArgs
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 AiFeatureStoreEntityTypeFeatureArgs
The arguments to resource properties.
opts ResourceOption
Bag of options to control resource's behavior.
name string
The unique name of the resource.
args AiFeatureStoreEntityTypeFeatureArgs
The arguments to resource properties.
opts CustomResourceOptions
Bag of options to control resource's behavior.
name String
The unique name of the resource.
args AiFeatureStoreEntityTypeFeatureArgs
The arguments to resource properties.
options CustomResourceOptions
Bag of options to control resource's behavior.

AiFeatureStoreEntityTypeFeature Resource Properties

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

Inputs

The AiFeatureStoreEntityTypeFeature resource accepts the following input properties:

Entitytype string

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

ValueType string

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

Description string

Description of the feature.

Labels Dictionary<string, string>

A set of key/value label pairs to assign to the feature.

Name string

The name of the feature. 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.

Entitytype string

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

ValueType string

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

Description string

Description of the feature.

Labels map[string]string

A set of key/value label pairs to assign to the feature.

Name string

The name of the feature. 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.

entitytype String

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

valueType String

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

description String

Description of the feature.

labels Map<String,String>

A set of key/value label pairs to assign to the feature.

name String

The name of the feature. 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.

entitytype string

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

valueType string

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

description string

Description of the feature.

labels {[key: string]: string}

A set of key/value label pairs to assign to the feature.

name string

The name of the feature. 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.

entitytype str

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

value_type str

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

description str

Description of the feature.

labels Mapping[str, str]

A set of key/value label pairs to assign to the feature.

name str

The name of the feature. 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.

entitytype String

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

valueType String

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

description String

Description of the feature.

labels Map<String>

A set of key/value label pairs to assign to the feature.

name String

The name of the feature. 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.

Outputs

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

CreateTime string

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

Etag string

Used to perform consistent read-modify-write updates.

Id string

The provider-assigned unique ID for this managed resource.

UpdateTime string

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

CreateTime string

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

Etag string

Used to perform consistent read-modify-write updates.

Id string

The provider-assigned unique ID for this managed resource.

UpdateTime string

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

createTime String

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

etag String

Used to perform consistent read-modify-write updates.

id String

The provider-assigned unique ID for this managed resource.

updateTime String

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

createTime string

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

etag string

Used to perform consistent read-modify-write updates.

id string

The provider-assigned unique ID for this managed resource.

updateTime string

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

create_time str

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

etag str

Used to perform consistent read-modify-write updates.

id str

The provider-assigned unique ID for this managed resource.

update_time str

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

createTime String

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

etag String

Used to perform consistent read-modify-write updates.

id String

The provider-assigned unique ID for this managed resource.

updateTime String

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

Look up Existing AiFeatureStoreEntityTypeFeature Resource

Get an existing AiFeatureStoreEntityTypeFeature resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: AiFeatureStoreEntityTypeFeatureState, opts?: CustomResourceOptions): AiFeatureStoreEntityTypeFeature
@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        create_time: Optional[str] = None,
        description: Optional[str] = None,
        entitytype: Optional[str] = None,
        etag: Optional[str] = None,
        labels: Optional[Mapping[str, str]] = None,
        name: Optional[str] = None,
        update_time: Optional[str] = None,
        value_type: Optional[str] = None) -> AiFeatureStoreEntityTypeFeature
func GetAiFeatureStoreEntityTypeFeature(ctx *Context, name string, id IDInput, state *AiFeatureStoreEntityTypeFeatureState, opts ...ResourceOption) (*AiFeatureStoreEntityTypeFeature, error)
public static AiFeatureStoreEntityTypeFeature Get(string name, Input<string> id, AiFeatureStoreEntityTypeFeatureState? state, CustomResourceOptions? opts = null)
public static AiFeatureStoreEntityTypeFeature get(String name, Output<String> id, AiFeatureStoreEntityTypeFeatureState state, CustomResourceOptions options)
Resource lookup is not supported in YAML
name
The unique name of the resulting resource.
id
The unique provider ID of the resource to lookup.
state
Any extra arguments used during the lookup.
opts
A bag of options that control this resource's behavior.
resource_name
The unique name of the resulting resource.
id
The unique provider ID of the resource to lookup.
name
The unique name of the resulting resource.
id
The unique provider ID of the resource to lookup.
state
Any extra arguments used during the lookup.
opts
A bag of options that control this resource's behavior.
name
The unique name of the resulting resource.
id
The unique provider ID of the resource to lookup.
state
Any extra arguments used during the lookup.
opts
A bag of options that control this resource's behavior.
name
The unique name of the resulting resource.
id
The unique provider ID of the resource to lookup.
state
Any extra arguments used during the lookup.
opts
A bag of options that control this resource's behavior.
The following state arguments are supported:
CreateTime string

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

Description string

Description of the feature.

Entitytype string

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

Etag string

Used to perform consistent read-modify-write updates.

Labels Dictionary<string, string>

A set of key/value label pairs to assign to the feature.

Name string

The name of the feature. 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.

UpdateTime string

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

ValueType string

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

CreateTime string

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

Description string

Description of the feature.

Entitytype string

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

Etag string

Used to perform consistent read-modify-write updates.

Labels map[string]string

A set of key/value label pairs to assign to the feature.

Name string

The name of the feature. 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.

UpdateTime string

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

ValueType string

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

createTime String

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

description String

Description of the feature.

entitytype String

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

etag String

Used to perform consistent read-modify-write updates.

labels Map<String,String>

A set of key/value label pairs to assign to the feature.

name String

The name of the feature. 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.

updateTime String

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

valueType String

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

createTime string

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

description string

Description of the feature.

entitytype string

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

etag string

Used to perform consistent read-modify-write updates.

labels {[key: string]: string}

A set of key/value label pairs to assign to the feature.

name string

The name of the feature. 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.

updateTime string

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

valueType string

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

create_time str

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

description str

Description of the feature.

entitytype str

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

etag str

Used to perform consistent read-modify-write updates.

labels Mapping[str, str]

A set of key/value label pairs to assign to the feature.

name str

The name of the feature. 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.

update_time str

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

value_type str

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

createTime String

The timestamp of when the entity type was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

description String

Description of the feature.

entitytype String

The name of the Featurestore to use, in the format projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entitytype}.

etag String

Used to perform consistent read-modify-write updates.

labels Map<String>

A set of key/value label pairs to assign to the feature.

name String

The name of the feature. 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.

updateTime String

The timestamp when the entity type was most recently updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

valueType String

Type of Feature value. Immutable. https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores.entityTypes.features#ValueType

Import

FeaturestoreEntitytypeFeature can be imported using any of these accepted formats

 $ pulumi import gcp:vertex/aiFeatureStoreEntityTypeFeature:AiFeatureStoreEntityTypeFeature default {{entitytype}}/features/{{name}}

Package Details

Repository
Google Cloud (GCP) Classic pulumi/pulumi-gcp
License
Apache-2.0
Notes

This Pulumi package is based on the google-beta Terraform Provider.