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  5. AiFeatureStore
Google Cloud Classic v6.67.0 published on Wednesday, Sep 27, 2023 by Pulumi
pulumi/pulumi-gcp

gcp.vertex.AiFeatureStore

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Google Cloud Classic v6.67.0 published on Wednesday, Sep 27, 2023 by Pulumi
pulumi/pulumi-gcp

    A collection of DataItems and Annotations on them.

    To get more information about Featurestore, see:

    Example Usage

    Vertex Ai Featurestore

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

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

});

    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 {
		_, err := vertex.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
			EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
				KmsKeyName: pulumi.String("kms-name"),
			},
			ForceDestroy: pulumi.Bool(true),
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
				FixedNodeCount: pulumi.Int(2),
			},
			Region: pulumi.String("us-central1"),
		})
		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.AiFeatureStoreEncryptionSpecArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
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()        
            .encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .forceDestroy(true)
            .labels(Map.of("foo", "bar"))
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .fixedNodeCount(2)
                .build())
            .region("us-central1")
            .build());

    }
}

    import pulumi
import pulumi_gcp as gcp

featurestore = gcp.vertex.AiFeatureStore("featurestore",
    encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
        kms_key_name="kms-name",
    ),
    force_destroy=True,
    labels={
        "foo": "bar",
    },
    online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
        fixed_node_count=2,
    ),
    region="us-central1")

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
    encryptionSpec: {
        kmsKeyName: "kms-name",
    },
    forceDestroy: true,
    labels: {
        foo: "bar",
    },
    onlineServingConfig: {
        fixedNodeCount: 2,
    },
    region: "us-central1",
});

    resources:
  featurestore:
    type: gcp:vertex:AiFeatureStore
    properties:
      encryptionSpec:
        kmsKeyName: kms-name
      forceDestroy: true
      labels:
        foo: bar
      onlineServingConfig:
        fixedNodeCount: 2
      region: us-central1

    Vertex Ai Featurestore With Beta Fields

    using System.Collections.Generic;
using System.Linq;
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,
        },
        EncryptionSpec = new Gcp.Vertex.Inputs.AiFeatureStoreEncryptionSpecArgs
        {
            KmsKeyName = "kms-name",
        },
        OnlineStorageTtlDays = 30,
        ForceDestroy = true,
    }, 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 {
		_, 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),
			},
			EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
				KmsKeyName: pulumi.String("kms-name"),
			},
			OnlineStorageTtlDays: pulumi.Int(30),
			ForceDestroy:         pulumi.Bool(true),
		}, 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.inputs.AiFeatureStoreEncryptionSpecArgs;
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())
            .encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .onlineStorageTtlDays(30)
            .forceDestroy(true)
            .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,
    ),
    encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
        kms_key_name="kms-name",
    ),
    online_storage_ttl_days=30,
    force_destroy=True,
    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,
    },
    encryptionSpec: {
        kmsKeyName: "kms-name",
    },
    onlineStorageTtlDays: 30,
    forceDestroy: true,
}, {
    provider: google_beta,
});

    resources:
  featurestore:
    type: gcp:vertex:AiFeatureStore
    properties:
      labels:
        foo: bar
      region: us-central1
      onlineServingConfig:
        fixedNodeCount: 2
      encryptionSpec:
        kmsKeyName: kms-name
      onlineStorageTtlDays: 30
      forceDestroy: true
    options:
      provider: ${["google-beta"]}

    Vertex Ai Featurestore Scaling

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

return await Deployment.RunAsync(() => 
{
    var featurestore = new Gcp.Vertex.AiFeatureStore("featurestore", new()
    {
        EncryptionSpec = new Gcp.Vertex.Inputs.AiFeatureStoreEncryptionSpecArgs
        {
            KmsKeyName = "kms-name",
        },
        ForceDestroy = true,
        Labels = 
        {
            { "foo", "bar" },
        },
        OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
        {
            Scaling = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigScalingArgs
            {
                MaxNodeCount = 10,
                MinNodeCount = 2,
            },
        },
        Region = "us-central1",
    });

});

    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 {
		_, err := vertex.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
			EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
				KmsKeyName: pulumi.String("kms-name"),
			},
			ForceDestroy: pulumi.Bool(true),
			Labels: pulumi.StringMap{
				"foo": pulumi.String("bar"),
			},
			OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
				Scaling: &vertex.AiFeatureStoreOnlineServingConfigScalingArgs{
					MaxNodeCount: pulumi.Int(10),
					MinNodeCount: pulumi.Int(2),
				},
			},
			Region: pulumi.String("us-central1"),
		})
		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.AiFeatureStoreEncryptionSpecArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigScalingArgs;
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()        
            .encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .forceDestroy(true)
            .labels(Map.of("foo", "bar"))
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .scaling(AiFeatureStoreOnlineServingConfigScalingArgs.builder()
                    .maxNodeCount(10)
                    .minNodeCount(2)
                    .build())
                .build())
            .region("us-central1")
            .build());

    }
}

    import pulumi
import pulumi_gcp as gcp

featurestore = gcp.vertex.AiFeatureStore("featurestore",
    encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
        kms_key_name="kms-name",
    ),
    force_destroy=True,
    labels={
        "foo": "bar",
    },
    online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
        scaling=gcp.vertex.AiFeatureStoreOnlineServingConfigScalingArgs(
            max_node_count=10,
            min_node_count=2,
        ),
    ),
    region="us-central1")

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
    encryptionSpec: {
        kmsKeyName: "kms-name",
    },
    forceDestroy: true,
    labels: {
        foo: "bar",
    },
    onlineServingConfig: {
        scaling: {
            maxNodeCount: 10,
            minNodeCount: 2,
        },
    },
    region: "us-central1",
});

    resources:
  featurestore:
    type: gcp:vertex:AiFeatureStore
    properties:
      encryptionSpec:
        kmsKeyName: kms-name
      forceDestroy: true
      labels:
        foo: bar
      onlineServingConfig:
        scaling:
          maxNodeCount: 10
          minNodeCount: 2
      region: us-central1

    Create AiFeatureStore Resource

    new AiFeatureStore(name: string, args?: AiFeatureStoreArgs, opts?: CustomResourceOptions);
    @overload
def AiFeatureStore(resource_name: str,
                   opts: Optional[ResourceOptions] = None,
                   encryption_spec: Optional[AiFeatureStoreEncryptionSpecArgs] = None,
                   force_destroy: Optional[bool] = None,
                   labels: Optional[Mapping[str, str]] = None,
                   name: Optional[str] = None,
                   online_serving_config: Optional[AiFeatureStoreOnlineServingConfigArgs] = None,
                   online_storage_ttl_days: Optional[int] = None,
                   project: Optional[str] = None,
                   region: Optional[str] = None)
@overload
def AiFeatureStore(resource_name: str,
                   args: Optional[AiFeatureStoreArgs] = None,
                   opts: Optional[ResourceOptions] = None)
    func NewAiFeatureStore(ctx *Context, name string, args *AiFeatureStoreArgs, opts ...ResourceOption) (*AiFeatureStore, error)
    public AiFeatureStore(string name, AiFeatureStoreArgs? args = null, CustomResourceOptions? opts = null)
    public AiFeatureStore(String name, AiFeatureStoreArgs args)
public AiFeatureStore(String name, AiFeatureStoreArgs args, CustomResourceOptions options)

    type: gcp:vertex:AiFeatureStore
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args AiFeatureStoreArgs
    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 AiFeatureStoreArgs
    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 AiFeatureStoreArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args AiFeatureStoreArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args AiFeatureStoreArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    AiFeatureStore 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 AiFeatureStore resource accepts the following input properties:

    EncryptionSpec AiFeatureStoreEncryptionSpec

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    ForceDestroy bool

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    Labels Dictionary<string, string>

    A set of key/value label pairs to assign to this Featurestore.

    Name string

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    OnlineServingConfig AiFeatureStoreOnlineServingConfig

    Config for online serving resources. Structure is documented below.

    OnlineStorageTtlDays int

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    Project string

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    Region string

    The region of the dataset. eg us-central1

    EncryptionSpec AiFeatureStoreEncryptionSpecArgs

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    ForceDestroy bool

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    Labels map[string]string

    A set of key/value label pairs to assign to this Featurestore.

    Name string

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    OnlineServingConfig AiFeatureStoreOnlineServingConfigArgs

    Config for online serving resources. Structure is documented below.

    OnlineStorageTtlDays int

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    Project string

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    Region string

    The region of the dataset. eg us-central1

    encryptionSpec AiFeatureStoreEncryptionSpec

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    forceDestroy Boolean

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels Map<String,String>

    A set of key/value label pairs to assign to this Featurestore.

    name String

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    onlineServingConfig AiFeatureStoreOnlineServingConfig

    Config for online serving resources. Structure is documented below.

    onlineStorageTtlDays Integer

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project String

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region String

    The region of the dataset. eg us-central1

    encryptionSpec AiFeatureStoreEncryptionSpec

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    forceDestroy boolean

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels {[key: string]: string}

    A set of key/value label pairs to assign to this Featurestore.

    name string

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    onlineServingConfig AiFeatureStoreOnlineServingConfig

    Config for online serving resources. Structure is documented below.

    onlineStorageTtlDays number

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project string

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region string

    The region of the dataset. eg us-central1

    encryption_spec AiFeatureStoreEncryptionSpecArgs

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    force_destroy bool

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels Mapping[str, str]

    A set of key/value label pairs to assign to this Featurestore.

    name str

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    online_serving_config AiFeatureStoreOnlineServingConfigArgs

    Config for online serving resources. Structure is documented below.

    online_storage_ttl_days int

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project str

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region str

    The region of the dataset. eg us-central1

    encryptionSpec Property Map

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    forceDestroy Boolean

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels Map<String>

    A set of key/value label pairs to assign to this Featurestore.

    name String

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    onlineServingConfig Property Map

    Config for online serving resources. Structure is documented below.

    onlineStorageTtlDays Number

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project String

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region String

    The region of the dataset. eg us-central1

    Outputs

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

    CreateTime string

    The timestamp of when the featurestore 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 of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    CreateTime string

    The timestamp of when the featurestore 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 of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    createTime String

    The timestamp of when the featurestore 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 of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    createTime string

    The timestamp of when the featurestore 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 of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    create_time str

    The timestamp of when the featurestore 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 of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    createTime String

    The timestamp of when the featurestore 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 of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    Look up Existing AiFeatureStore Resource

    Get an existing AiFeatureStore 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?: AiFeatureStoreState, opts?: CustomResourceOptions): AiFeatureStore
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        create_time: Optional[str] = None,
        encryption_spec: Optional[AiFeatureStoreEncryptionSpecArgs] = None,
        etag: Optional[str] = None,
        force_destroy: Optional[bool] = None,
        labels: Optional[Mapping[str, str]] = None,
        name: Optional[str] = None,
        online_serving_config: Optional[AiFeatureStoreOnlineServingConfigArgs] = None,
        online_storage_ttl_days: Optional[int] = None,
        project: Optional[str] = None,
        region: Optional[str] = None,
        update_time: Optional[str] = None) -> AiFeatureStore
    func GetAiFeatureStore(ctx *Context, name string, id IDInput, state *AiFeatureStoreState, opts ...ResourceOption) (*AiFeatureStore, error)
    public static AiFeatureStore Get(string name, Input<string> id, AiFeatureStoreState? state, CustomResourceOptions? opts = null)
    public static AiFeatureStore get(String name, Output<String> id, AiFeatureStoreState 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 featurestore was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    EncryptionSpec AiFeatureStoreEncryptionSpec

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    Etag string

    Used to perform consistent read-modify-write updates.

    ForceDestroy bool

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    Labels Dictionary<string, string>

    A set of key/value label pairs to assign to this Featurestore.

    Name string

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    OnlineServingConfig AiFeatureStoreOnlineServingConfig

    Config for online serving resources. Structure is documented below.

    OnlineStorageTtlDays int

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    Project string

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    Region string

    The region of the dataset. eg us-central1

    UpdateTime string

    The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    CreateTime string

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

    EncryptionSpec AiFeatureStoreEncryptionSpecArgs

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    Etag string

    Used to perform consistent read-modify-write updates.

    ForceDestroy bool

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    Labels map[string]string

    A set of key/value label pairs to assign to this Featurestore.

    Name string

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    OnlineServingConfig AiFeatureStoreOnlineServingConfigArgs

    Config for online serving resources. Structure is documented below.

    OnlineStorageTtlDays int

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    Project string

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    Region string

    The region of the dataset. eg us-central1

    UpdateTime string

    The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    createTime String

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

    encryptionSpec AiFeatureStoreEncryptionSpec

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    etag String

    Used to perform consistent read-modify-write updates.

    forceDestroy Boolean

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels Map<String,String>

    A set of key/value label pairs to assign to this Featurestore.

    name String

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    onlineServingConfig AiFeatureStoreOnlineServingConfig

    Config for online serving resources. Structure is documented below.

    onlineStorageTtlDays Integer

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project String

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region String

    The region of the dataset. eg us-central1

    updateTime String

    The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    createTime string

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

    encryptionSpec AiFeatureStoreEncryptionSpec

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    etag string

    Used to perform consistent read-modify-write updates.

    forceDestroy boolean

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels {[key: string]: string}

    A set of key/value label pairs to assign to this Featurestore.

    name string

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    onlineServingConfig AiFeatureStoreOnlineServingConfig

    Config for online serving resources. Structure is documented below.

    onlineStorageTtlDays number

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project string

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region string

    The region of the dataset. eg us-central1

    updateTime string

    The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    create_time str

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

    encryption_spec AiFeatureStoreEncryptionSpecArgs

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    etag str

    Used to perform consistent read-modify-write updates.

    force_destroy bool

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels Mapping[str, str]

    A set of key/value label pairs to assign to this Featurestore.

    name str

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    online_serving_config AiFeatureStoreOnlineServingConfigArgs

    Config for online serving resources. Structure is documented below.

    online_storage_ttl_days int

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project str

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region str

    The region of the dataset. eg us-central1

    update_time str

    The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    createTime String

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

    encryptionSpec Property Map

    If set, both of the online and offline data storage will be secured by this key. Structure is documented below.

    etag String

    Used to perform consistent read-modify-write updates.

    forceDestroy Boolean

    If set to true, any EntityTypes and Features for this Featurestore will also be deleted

    labels Map<String>

    A set of key/value label pairs to assign to this Featurestore.

    name String

    The name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

    onlineServingConfig Property Map

    Config for online serving resources. Structure is documented below.

    onlineStorageTtlDays Number

    TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days

    project String

    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

    region String

    The region of the dataset. eg us-central1

    updateTime String

    The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    Supporting Types

    AiFeatureStoreEncryptionSpec, AiFeatureStoreEncryptionSpecArgs

    KmsKeyName string

    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    KmsKeyName string

    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    kmsKeyName String

    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    kmsKeyName string

    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    kms_key_name str

    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    kmsKeyName String

    The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.

    AiFeatureStoreOnlineServingConfig, AiFeatureStoreOnlineServingConfigArgs

    FixedNodeCount int

    The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.

    Scaling AiFeatureStoreOnlineServingConfigScaling

    Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.

    FixedNodeCount int

    The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.

    Scaling AiFeatureStoreOnlineServingConfigScaling

    Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.

    fixedNodeCount Integer

    The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.

    scaling AiFeatureStoreOnlineServingConfigScaling

    Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.

    fixedNodeCount number

    The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.

    scaling AiFeatureStoreOnlineServingConfigScaling

    Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.

    fixed_node_count int

    The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.

    scaling AiFeatureStoreOnlineServingConfigScaling

    Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.

    fixedNodeCount Number

    The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.

    scaling Property Map

    Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.

    AiFeatureStoreOnlineServingConfigScaling, AiFeatureStoreOnlineServingConfigScalingArgs

    MaxNodeCount int

    The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.

    MinNodeCount int

    The minimum number of nodes to scale down to. Must be greater than or equal to 1.

    MaxNodeCount int

    The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.

    MinNodeCount int

    The minimum number of nodes to scale down to. Must be greater than or equal to 1.

    maxNodeCount Integer

    The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.

    minNodeCount Integer

    The minimum number of nodes to scale down to. Must be greater than or equal to 1.

    maxNodeCount number

    The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.

    minNodeCount number

    The minimum number of nodes to scale down to. Must be greater than or equal to 1.

    max_node_count int

    The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.

    min_node_count int

    The minimum number of nodes to scale down to. Must be greater than or equal to 1.

    maxNodeCount Number

    The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.

    minNodeCount Number

    The minimum number of nodes to scale down to. Must be greater than or equal to 1.

    Import

    Featurestore can be imported using any of these accepted formats

     $ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default projects/{{project}}/locations/{{region}}/featurestores/{{name}}

     $ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default {{project}}/{{region}}/{{name}}

     $ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default {{region}}/{{name}}

     $ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default {{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.

    gcp logo
    Google Cloud Classic v6.67.0 published on Wednesday, Sep 27, 2023 by Pulumi
    pulumi/pulumi-gcp