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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
@file:Suppress("NAME_SHADOWING", "DEPRECATION")
package com.pulumi.gcp.vertex.kotlin
import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.gcp.vertex.AiFeatureOnlineStoreArgs.builder
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreBigtableArgs
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreBigtableArgsBuilder
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreDedicatedServingEndpointArgs
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreDedicatedServingEndpointArgsBuilder
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreEmbeddingManagementArgs
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreEmbeddingManagementArgsBuilder
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreOptimizedArgs
import com.pulumi.gcp.vertex.kotlin.inputs.AiFeatureOnlineStoreOptimizedArgsBuilder
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiTagMarker
import com.pulumi.kotlin.applySuspend
import kotlin.Boolean
import kotlin.Pair
import kotlin.String
import kotlin.Suppress
import kotlin.Unit
import kotlin.collections.Map
import kotlin.jvm.JvmName
/**
* Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.
* To get more information about FeatureOnlineStore, see:
* * [API documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featureOnlineStores)
* * How-to Guides
* * [Official Documentation](https://cloud.google.com/vertex-ai/docs)
* ## Example Usage
* ### Vertex Ai Feature Online Store
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
* const featureOnlineStore = new gcp.vertex.AiFeatureOnlineStore("feature_online_store", {
* name: "example_feature_online_store",
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* bigtable: {
* autoScaling: {
* minNodeCount: 1,
* maxNodeCount: 3,
* cpuUtilizationTarget: 50,
* },
* },
* });
* ```
* ```python
* import pulumi
* import pulumi_gcp as gcp
* feature_online_store = gcp.vertex.AiFeatureOnlineStore("feature_online_store",
* name="example_feature_online_store",
* labels={
* "foo": "bar",
* },
* region="us-central1",
* bigtable=gcp.vertex.AiFeatureOnlineStoreBigtableArgs(
* auto_scaling=gcp.vertex.AiFeatureOnlineStoreBigtableAutoScalingArgs(
* min_node_count=1,
* max_node_count=3,
* cpu_utilization_target=50,
* ),
* ))
* ```
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using Gcp = Pulumi.Gcp;
* return await Deployment.RunAsync(() =>
* {
* var featureOnlineStore = new Gcp.Vertex.AiFeatureOnlineStore("feature_online_store", new()
* {
* Name = "example_feature_online_store",
* Labels =
* {
* { "foo", "bar" },
* },
* Region = "us-central1",
* Bigtable = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreBigtableArgs
* {
* AutoScaling = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreBigtableAutoScalingArgs
* {
* MinNodeCount = 1,
* MaxNodeCount = 3,
* CpuUtilizationTarget = 50,
* },
* },
* });
* });
* ```
* ```go
* package main
* import (
* "github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/vertex"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := vertex.NewAiFeatureOnlineStore(ctx, "feature_online_store", &vertex.AiFeatureOnlineStoreArgs{
* Name: pulumi.String("example_feature_online_store"),
* Labels: pulumi.StringMap{
* "foo": pulumi.String("bar"),
* },
* Region: pulumi.String("us-central1"),
* Bigtable: &vertex.AiFeatureOnlineStoreBigtableArgs{
* AutoScaling: &vertex.AiFeatureOnlineStoreBigtableAutoScalingArgs{
* MinNodeCount: pulumi.Int(1),
* MaxNodeCount: pulumi.Int(3),
* CpuUtilizationTarget: pulumi.Int(50),
* },
* },
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.gcp.vertex.AiFeatureOnlineStore;
* import com.pulumi.gcp.vertex.AiFeatureOnlineStoreArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreBigtableArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreBigtableAutoScalingArgs;
* 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 featureOnlineStore = new AiFeatureOnlineStore("featureOnlineStore", AiFeatureOnlineStoreArgs.builder()
* .name("example_feature_online_store")
* .labels(Map.of("foo", "bar"))
* .region("us-central1")
* .bigtable(AiFeatureOnlineStoreBigtableArgs.builder()
* .autoScaling(AiFeatureOnlineStoreBigtableAutoScalingArgs.builder()
* .minNodeCount(1)
* .maxNodeCount(3)
* .cpuUtilizationTarget(50)
* .build())
* .build())
* .build());
* }
* }
* ```
* ```yaml
* resources:
* featureOnlineStore:
* type: gcp:vertex:AiFeatureOnlineStore
* name: feature_online_store
* properties:
* name: example_feature_online_store
* labels:
* foo: bar
* region: us-central1
* bigtable:
* autoScaling:
* minNodeCount: 1
* maxNodeCount: 3
* cpuUtilizationTarget: 50
* ```
*
* ### Vertex Ai Featureonlinestore With Beta Fields Optimized
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
* const project = gcp.organizations.getProject({});
* const featureonlinestore = new gcp.vertex.AiFeatureOnlineStore("featureonlinestore", {
* name: "example_feature_online_store_optimized",
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* optimized: {},
* dedicatedServingEndpoint: {
* privateServiceConnectConfig: {
* enablePrivateServiceConnect: true,
* projectAllowlists: [project.then(project => project.number)],
* },
* },
* });
* ```
* ```python
* import pulumi
* import pulumi_gcp as gcp
* project = gcp.organizations.get_project()
* featureonlinestore = gcp.vertex.AiFeatureOnlineStore("featureonlinestore",
* name="example_feature_online_store_optimized",
* labels={
* "foo": "bar",
* },
* region="us-central1",
* optimized=gcp.vertex.AiFeatureOnlineStoreOptimizedArgs(),
* dedicated_serving_endpoint=gcp.vertex.AiFeatureOnlineStoreDedicatedServingEndpointArgs(
* private_service_connect_config=gcp.vertex.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs(
* enable_private_service_connect=True,
* project_allowlists=[project.number],
* ),
* ))
* ```
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using Gcp = Pulumi.Gcp;
* return await Deployment.RunAsync(() =>
* {
* var project = Gcp.Organizations.GetProject.Invoke();
* var featureonlinestore = new Gcp.Vertex.AiFeatureOnlineStore("featureonlinestore", new()
* {
* Name = "example_feature_online_store_optimized",
* Labels =
* {
* { "foo", "bar" },
* },
* Region = "us-central1",
* Optimized = null,
* DedicatedServingEndpoint = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreDedicatedServingEndpointArgs
* {
* PrivateServiceConnectConfig = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs
* {
* EnablePrivateServiceConnect = true,
* ProjectAllowlists = new[]
* {
* project.Apply(getProjectResult => getProjectResult.Number),
* },
* },
* },
* });
* });
* ```
* ```go
* package main
* import (
* "github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/organizations"
* "github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/vertex"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* project, err := organizations.LookupProject(ctx, nil, nil)
* if err != nil {
* return err
* }
* _, err = vertex.NewAiFeatureOnlineStore(ctx, "featureonlinestore", &vertex.AiFeatureOnlineStoreArgs{
* Name: pulumi.String("example_feature_online_store_optimized"),
* Labels: pulumi.StringMap{
* "foo": pulumi.String("bar"),
* },
* Region: pulumi.String("us-central1"),
* Optimized: nil,
* DedicatedServingEndpoint: &vertex.AiFeatureOnlineStoreDedicatedServingEndpointArgs{
* PrivateServiceConnectConfig: &vertex.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs{
* EnablePrivateServiceConnect: pulumi.Bool(true),
* ProjectAllowlists: pulumi.StringArray{
* pulumi.String(project.Number),
* },
* },
* },
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.gcp.organizations.OrganizationsFunctions;
* import com.pulumi.gcp.organizations.inputs.GetProjectArgs;
* import com.pulumi.gcp.vertex.AiFeatureOnlineStore;
* import com.pulumi.gcp.vertex.AiFeatureOnlineStoreArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreOptimizedArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreDedicatedServingEndpointArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs;
* 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) {
* final var project = OrganizationsFunctions.getProject();
* var featureonlinestore = new AiFeatureOnlineStore("featureonlinestore", AiFeatureOnlineStoreArgs.builder()
* .name("example_feature_online_store_optimized")
* .labels(Map.of("foo", "bar"))
* .region("us-central1")
* .optimized()
* .dedicatedServingEndpoint(AiFeatureOnlineStoreDedicatedServingEndpointArgs.builder()
* .privateServiceConnectConfig(AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs.builder()
* .enablePrivateServiceConnect(true)
* .projectAllowlists(project.applyValue(getProjectResult -> getProjectResult.number()))
* .build())
* .build())
* .build());
* }
* }
* ```
* ```yaml
* resources:
* featureonlinestore:
* type: gcp:vertex:AiFeatureOnlineStore
* properties:
* name: example_feature_online_store_optimized
* labels:
* foo: bar
* region: us-central1
* optimized: {}
* dedicatedServingEndpoint:
* privateServiceConnectConfig:
* enablePrivateServiceConnect: true
* projectAllowlists:
* - ${project.number}
* variables:
* project:
* fn::invoke:
* Function: gcp:organizations:getProject
* Arguments: {}
* ```
*
* ### Vertex Ai Featureonlinestore With Beta Fields Bigtable
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
* const featureonlinestore = new gcp.vertex.AiFeatureOnlineStore("featureonlinestore", {
* name: "example_feature_online_store_beta_bigtable",
* labels: {
* foo: "bar",
* },
* region: "us-central1",
* bigtable: {
* autoScaling: {
* minNodeCount: 1,
* maxNodeCount: 2,
* cpuUtilizationTarget: 80,
* },
* },
* embeddingManagement: {
* enabled: true,
* },
* forceDestroy: true,
* });
* const project = gcp.organizations.getProject({});
* ```
* ```python
* import pulumi
* import pulumi_gcp as gcp
* featureonlinestore = gcp.vertex.AiFeatureOnlineStore("featureonlinestore",
* name="example_feature_online_store_beta_bigtable",
* labels={
* "foo": "bar",
* },
* region="us-central1",
* bigtable=gcp.vertex.AiFeatureOnlineStoreBigtableArgs(
* auto_scaling=gcp.vertex.AiFeatureOnlineStoreBigtableAutoScalingArgs(
* min_node_count=1,
* max_node_count=2,
* cpu_utilization_target=80,
* ),
* ),
* embedding_management=gcp.vertex.AiFeatureOnlineStoreEmbeddingManagementArgs(
* enabled=True,
* ),
* force_destroy=True)
* project = gcp.organizations.get_project()
* ```
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using Gcp = Pulumi.Gcp;
* return await Deployment.RunAsync(() =>
* {
* var featureonlinestore = new Gcp.Vertex.AiFeatureOnlineStore("featureonlinestore", new()
* {
* Name = "example_feature_online_store_beta_bigtable",
* Labels =
* {
* { "foo", "bar" },
* },
* Region = "us-central1",
* Bigtable = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreBigtableArgs
* {
* AutoScaling = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreBigtableAutoScalingArgs
* {
* MinNodeCount = 1,
* MaxNodeCount = 2,
* CpuUtilizationTarget = 80,
* },
* },
* EmbeddingManagement = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreEmbeddingManagementArgs
* {
* Enabled = true,
* },
* ForceDestroy = true,
* });
* var project = Gcp.Organizations.GetProject.Invoke();
* });
* ```
* ```go
* package main
* import (
* "github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/organizations"
* "github.com/pulumi/pulumi-gcp/sdk/v7/go/gcp/vertex"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := vertex.NewAiFeatureOnlineStore(ctx, "featureonlinestore", &vertex.AiFeatureOnlineStoreArgs{
* Name: pulumi.String("example_feature_online_store_beta_bigtable"),
* Labels: pulumi.StringMap{
* "foo": pulumi.String("bar"),
* },
* Region: pulumi.String("us-central1"),
* Bigtable: &vertex.AiFeatureOnlineStoreBigtableArgs{
* AutoScaling: &vertex.AiFeatureOnlineStoreBigtableAutoScalingArgs{
* MinNodeCount: pulumi.Int(1),
* MaxNodeCount: pulumi.Int(2),
* CpuUtilizationTarget: pulumi.Int(80),
* },
* },
* EmbeddingManagement: &vertex.AiFeatureOnlineStoreEmbeddingManagementArgs{
* Enabled: pulumi.Bool(true),
* },
* ForceDestroy: pulumi.Bool(true),
* })
* if err != nil {
* return err
* }
* _, err = organizations.LookupProject(ctx, nil, nil)
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.gcp.vertex.AiFeatureOnlineStore;
* import com.pulumi.gcp.vertex.AiFeatureOnlineStoreArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreBigtableArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreBigtableAutoScalingArgs;
* import com.pulumi.gcp.vertex.inputs.AiFeatureOnlineStoreEmbeddingManagementArgs;
* import com.pulumi.gcp.organizations.OrganizationsFunctions;
* import com.pulumi.gcp.organizations.inputs.GetProjectArgs;
* 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 featureonlinestore = new AiFeatureOnlineStore("featureonlinestore", AiFeatureOnlineStoreArgs.builder()
* .name("example_feature_online_store_beta_bigtable")
* .labels(Map.of("foo", "bar"))
* .region("us-central1")
* .bigtable(AiFeatureOnlineStoreBigtableArgs.builder()
* .autoScaling(AiFeatureOnlineStoreBigtableAutoScalingArgs.builder()
* .minNodeCount(1)
* .maxNodeCount(2)
* .cpuUtilizationTarget(80)
* .build())
* .build())
* .embeddingManagement(AiFeatureOnlineStoreEmbeddingManagementArgs.builder()
* .enabled(true)
* .build())
* .forceDestroy(true)
* .build());
* final var project = OrganizationsFunctions.getProject();
* }
* }
* ```
* ```yaml
* resources:
* featureonlinestore:
* type: gcp:vertex:AiFeatureOnlineStore
* properties:
* name: example_feature_online_store_beta_bigtable
* labels:
* foo: bar
* region: us-central1
* bigtable:
* autoScaling:
* minNodeCount: 1
* maxNodeCount: 2
* cpuUtilizationTarget: 80
* embeddingManagement:
* enabled: true
* forceDestroy: true
* variables:
* project:
* fn::invoke:
* Function: gcp:organizations:getProject
* Arguments: {}
* ```
*
* ## Import
* FeatureOnlineStore can be imported using any of these accepted formats:
* * `projects/{{project}}/locations/{{region}}/featureOnlineStores/{{name}}`
* * `{{project}}/{{region}}/{{name}}`
* * `{{region}}/{{name}}`
* * `{{name}}`
* When using the `pulumi import` command, FeatureOnlineStore can be imported using one of the formats above. For example:
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default projects/{{project}}/locations/{{region}}/featureOnlineStores/{{name}}
* ```
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default {{project}}/{{region}}/{{name}}
* ```
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default {{region}}/{{name}}
* ```
* ```sh
* $ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default {{name}}
* ```
* @property bigtable Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
* Structure is documented below.
* @property dedicatedServingEndpoint The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default.
* Structure is documented below.
* @property embeddingManagement The settings for embedding management in FeatureOnlineStore. Embedding management can only be used with BigTable.
* Structure is documented below.
* @property forceDestroy If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
* @property labels The labels with user-defined metadata to organize your feature online stores.
* **Note**: This field is non-authoritative, and will only manage the labels present in your configuration.
* Please refer to the field `effective_labels` for all of the labels present on the resource.
* @property name The resource name of the Feature Online Store. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
* - - -
* @property optimized Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
* @property project The ID of the project in which the resource belongs.
* If it is not provided, the provider project is used.
* @property region The region of feature online store. eg us-central1
*/
public data class AiFeatureOnlineStoreArgs(
public val bigtable: Output? = null,
public val dedicatedServingEndpoint: Output? =
null,
public val embeddingManagement: Output? = null,
public val forceDestroy: Output? = null,
public val labels: Output>? = null,
public val name: Output? = null,
public val optimized: Output? = null,
public val project: Output? = null,
public val region: Output? = null,
) : ConvertibleToJava {
override fun toJava(): com.pulumi.gcp.vertex.AiFeatureOnlineStoreArgs =
com.pulumi.gcp.vertex.AiFeatureOnlineStoreArgs.builder()
.bigtable(bigtable?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) }))
.dedicatedServingEndpoint(
dedicatedServingEndpoint?.applyValue({ args0 ->
args0.let({ args0 ->
args0.toJava()
})
}),
)
.embeddingManagement(
embeddingManagement?.applyValue({ args0 ->
args0.let({ args0 ->
args0.toJava()
})
}),
)
.forceDestroy(forceDestroy?.applyValue({ args0 -> args0 }))
.labels(labels?.applyValue({ args0 -> args0.map({ args0 -> args0.key.to(args0.value) }).toMap() }))
.name(name?.applyValue({ args0 -> args0 }))
.optimized(optimized?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) }))
.project(project?.applyValue({ args0 -> args0 }))
.region(region?.applyValue({ args0 -> args0 })).build()
}
/**
* Builder for [AiFeatureOnlineStoreArgs].
*/
@PulumiTagMarker
public class AiFeatureOnlineStoreArgsBuilder internal constructor() {
private var bigtable: Output? = null
private var dedicatedServingEndpoint: Output? =
null
private var embeddingManagement: Output? = null
private var forceDestroy: Output? = null
private var labels: Output>? = null
private var name: Output? = null
private var optimized: Output? = null
private var project: Output? = null
private var region: Output? = null
/**
* @param value Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
* Structure is documented below.
*/
@JvmName("dgowbalhevcpabhv")
public suspend fun bigtable(`value`: Output) {
this.bigtable = value
}
/**
* @param value The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default.
* Structure is documented below.
*/
@JvmName("mfsxigbjlapgvviy")
public suspend fun dedicatedServingEndpoint(`value`: Output) {
this.dedicatedServingEndpoint = value
}
/**
* @param value The settings for embedding management in FeatureOnlineStore. Embedding management can only be used with BigTable.
* Structure is documented below.
*/
@JvmName("vigtveudoecrcmnb")
public suspend fun embeddingManagement(`value`: Output) {
this.embeddingManagement = value
}
/**
* @param value If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
*/
@JvmName("tlomrthukuhmjmhf")
public suspend fun forceDestroy(`value`: Output) {
this.forceDestroy = value
}
/**
* @param value The labels with user-defined metadata to organize your feature online stores.
* **Note**: This field is non-authoritative, and will only manage the labels present in your configuration.
* Please refer to the field `effective_labels` for all of the labels present on the resource.
*/
@JvmName("sthcbijgmswwsuri")
public suspend fun labels(`value`: Output>) {
this.labels = value
}
/**
* @param value The resource name of the Feature Online Store. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
* - - -
*/
@JvmName("qquxxlpdolrxjlii")
public suspend fun name(`value`: Output) {
this.name = value
}
/**
* @param value Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
*/
@JvmName("clrjcjetjhpckwsp")
public suspend fun optimized(`value`: Output) {
this.optimized = value
}
/**
* @param value The ID of the project in which the resource belongs.
* If it is not provided, the provider project is used.
*/
@JvmName("xgfpjogerujblabn")
public suspend fun project(`value`: Output) {
this.project = value
}
/**
* @param value The region of feature online store. eg us-central1
*/
@JvmName("xeqbchrdykvluegg")
public suspend fun region(`value`: Output) {
this.region = value
}
/**
* @param value Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
* Structure is documented below.
*/
@JvmName("wapfrrfanfdfoxnc")
public suspend fun bigtable(`value`: AiFeatureOnlineStoreBigtableArgs?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.bigtable = mapped
}
/**
* @param argument Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
* Structure is documented below.
*/
@JvmName("hbvtfthksbfdjfmv")
public suspend fun bigtable(argument: suspend AiFeatureOnlineStoreBigtableArgsBuilder.() -> Unit) {
val toBeMapped = AiFeatureOnlineStoreBigtableArgsBuilder().applySuspend { argument() }.build()
val mapped = of(toBeMapped)
this.bigtable = mapped
}
/**
* @param value The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default.
* Structure is documented below.
*/
@JvmName("qkjeqytinbnbsuda")
public suspend fun dedicatedServingEndpoint(`value`: AiFeatureOnlineStoreDedicatedServingEndpointArgs?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.dedicatedServingEndpoint = mapped
}
/**
* @param argument The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default.
* Structure is documented below.
*/
@JvmName("yvimuguhnggunvdh")
public suspend fun dedicatedServingEndpoint(argument: suspend AiFeatureOnlineStoreDedicatedServingEndpointArgsBuilder.() -> Unit) {
val toBeMapped = AiFeatureOnlineStoreDedicatedServingEndpointArgsBuilder().applySuspend {
argument()
}.build()
val mapped = of(toBeMapped)
this.dedicatedServingEndpoint = mapped
}
/**
* @param value The settings for embedding management in FeatureOnlineStore. Embedding management can only be used with BigTable.
* Structure is documented below.
*/
@JvmName("xpepqfpudschdnfw")
public suspend fun embeddingManagement(`value`: AiFeatureOnlineStoreEmbeddingManagementArgs?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.embeddingManagement = mapped
}
/**
* @param argument The settings for embedding management in FeatureOnlineStore. Embedding management can only be used with BigTable.
* Structure is documented below.
*/
@JvmName("wnwdovesniihewdx")
public suspend fun embeddingManagement(argument: suspend AiFeatureOnlineStoreEmbeddingManagementArgsBuilder.() -> Unit) {
val toBeMapped = AiFeatureOnlineStoreEmbeddingManagementArgsBuilder().applySuspend {
argument()
}.build()
val mapped = of(toBeMapped)
this.embeddingManagement = mapped
}
/**
* @param value If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
*/
@JvmName("oltqytuvsmxsxklc")
public suspend fun forceDestroy(`value`: Boolean?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.forceDestroy = mapped
}
/**
* @param value The labels with user-defined metadata to organize your feature online stores.
* **Note**: This field is non-authoritative, and will only manage the labels present in your configuration.
* Please refer to the field `effective_labels` for all of the labels present on the resource.
*/
@JvmName("hkwldingutjfgbcf")
public suspend fun labels(`value`: Map?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.labels = mapped
}
/**
* @param values The labels with user-defined metadata to organize your feature online stores.
* **Note**: This field is non-authoritative, and will only manage the labels present in your configuration.
* Please refer to the field `effective_labels` for all of the labels present on the resource.
*/
@JvmName("ylpbjwgtlijminho")
public fun labels(vararg values: Pair) {
val toBeMapped = values.toMap()
val mapped = toBeMapped.let({ args0 -> of(args0) })
this.labels = mapped
}
/**
* @param value The resource name of the Feature Online Store. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
* - - -
*/
@JvmName("diqxbuubagmduiwq")
public suspend fun name(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.name = mapped
}
/**
* @param value Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
*/
@JvmName("pcqxkjuqnrfsnora")
public suspend fun optimized(`value`: AiFeatureOnlineStoreOptimizedArgs?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.optimized = mapped
}
/**
* @param argument Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
*/
@JvmName("othmaevmifrvnkqa")
public suspend fun optimized(argument: suspend AiFeatureOnlineStoreOptimizedArgsBuilder.() -> Unit) {
val toBeMapped = AiFeatureOnlineStoreOptimizedArgsBuilder().applySuspend { argument() }.build()
val mapped = of(toBeMapped)
this.optimized = mapped
}
/**
* @param value The ID of the project in which the resource belongs.
* If it is not provided, the provider project is used.
*/
@JvmName("nchuiifqhclivgns")
public suspend fun project(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.project = mapped
}
/**
* @param value The region of feature online store. eg us-central1
*/
@JvmName("wfwitecmiqebsett")
public suspend fun region(`value`: String?) {
val toBeMapped = value
val mapped = toBeMapped?.let({ args0 -> of(args0) })
this.region = mapped
}
internal fun build(): AiFeatureOnlineStoreArgs = AiFeatureOnlineStoreArgs(
bigtable = bigtable,
dedicatedServingEndpoint = dedicatedServingEndpoint,
embeddingManagement = embeddingManagement,
forceDestroy = forceDestroy,
labels = labels,
name = name,
optimized = optimized,
project = project,
region = region,
)
}
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