gcp.vertex.AiFeatureOnlineStore
Explore with Pulumi AI
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
- How-to Guides
Example Usage
Vertex Ai Feature Online Store
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,
},
},
});
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={
"auto_scaling": {
"min_node_count": 1,
"max_node_count": 3,
"cpu_utilization_target": 50,
},
})
package main
import (
"github.com/pulumi/pulumi-gcp/sdk/v8/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
})
}
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,
},
},
});
});
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());
}
}
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 Optimized
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)],
},
},
});
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={},
dedicated_serving_endpoint={
"private_service_connect_config": {
"enable_private_service_connect": True,
"project_allowlists": [project.number],
},
})
package main
import (
"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/organizations"
"github.com/pulumi/pulumi-gcp/sdk/v8/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, &organizations.LookupProjectArgs{}, 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: &vertex.AiFeatureOnlineStoreOptimizedArgs{},
DedicatedServingEndpoint: &vertex.AiFeatureOnlineStoreDedicatedServingEndpointArgs{
PrivateServiceConnectConfig: &vertex.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs{
EnablePrivateServiceConnect: pulumi.Bool(true),
ProjectAllowlists: pulumi.StringArray{
pulumi.String(project.Number),
},
},
},
})
if err != nil {
return err
}
return nil
})
}
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),
},
},
},
});
});
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());
}
}
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
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({});
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={
"auto_scaling": {
"min_node_count": 1,
"max_node_count": 2,
"cpu_utilization_target": 80,
},
},
embedding_management={
"enabled": True,
},
force_destroy=True)
project = gcp.organizations.get_project()
package main
import (
"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/organizations"
"github.com/pulumi/pulumi-gcp/sdk/v8/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, &organizations.LookupProjectArgs{}, nil)
if err != nil {
return err
}
return nil
})
}
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();
});
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();
}
}
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: {}
Create AiFeatureOnlineStore Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new AiFeatureOnlineStore(name: string, args?: AiFeatureOnlineStoreArgs, opts?: CustomResourceOptions);
@overload
def AiFeatureOnlineStore(resource_name: str,
args: Optional[AiFeatureOnlineStoreArgs] = None,
opts: Optional[ResourceOptions] = None)
@overload
def AiFeatureOnlineStore(resource_name: str,
opts: Optional[ResourceOptions] = None,
bigtable: Optional[AiFeatureOnlineStoreBigtableArgs] = None,
dedicated_serving_endpoint: Optional[AiFeatureOnlineStoreDedicatedServingEndpointArgs] = None,
embedding_management: Optional[AiFeatureOnlineStoreEmbeddingManagementArgs] = None,
force_destroy: Optional[bool] = None,
labels: Optional[Mapping[str, str]] = None,
name: Optional[str] = None,
optimized: Optional[AiFeatureOnlineStoreOptimizedArgs] = None,
project: Optional[str] = None,
region: Optional[str] = None)
func NewAiFeatureOnlineStore(ctx *Context, name string, args *AiFeatureOnlineStoreArgs, opts ...ResourceOption) (*AiFeatureOnlineStore, error)
public AiFeatureOnlineStore(string name, AiFeatureOnlineStoreArgs? args = null, CustomResourceOptions? opts = null)
public AiFeatureOnlineStore(String name, AiFeatureOnlineStoreArgs args)
public AiFeatureOnlineStore(String name, AiFeatureOnlineStoreArgs args, CustomResourceOptions options)
type: gcp:vertex:AiFeatureOnlineStore
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args AiFeatureOnlineStoreArgs
- 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 AiFeatureOnlineStoreArgs
- 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 AiFeatureOnlineStoreArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args AiFeatureOnlineStoreArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args AiFeatureOnlineStoreArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var aiFeatureOnlineStoreResource = new Gcp.Vertex.AiFeatureOnlineStore("aiFeatureOnlineStoreResource", new()
{
Bigtable = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreBigtableArgs
{
AutoScaling = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreBigtableAutoScalingArgs
{
MaxNodeCount = 0,
MinNodeCount = 0,
CpuUtilizationTarget = 0,
},
},
DedicatedServingEndpoint = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreDedicatedServingEndpointArgs
{
PrivateServiceConnectConfig = new Gcp.Vertex.Inputs.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs
{
EnablePrivateServiceConnect = false,
ProjectAllowlists = new[]
{
"string",
},
},
PublicEndpointDomainName = "string",
ServiceAttachment = "string",
},
ForceDestroy = false,
Labels =
{
{ "string", "string" },
},
Name = "string",
Optimized = null,
Project = "string",
Region = "string",
});
example, err := vertex.NewAiFeatureOnlineStore(ctx, "aiFeatureOnlineStoreResource", &vertex.AiFeatureOnlineStoreArgs{
Bigtable: &vertex.AiFeatureOnlineStoreBigtableArgs{
AutoScaling: &vertex.AiFeatureOnlineStoreBigtableAutoScalingArgs{
MaxNodeCount: pulumi.Int(0),
MinNodeCount: pulumi.Int(0),
CpuUtilizationTarget: pulumi.Int(0),
},
},
DedicatedServingEndpoint: &vertex.AiFeatureOnlineStoreDedicatedServingEndpointArgs{
PrivateServiceConnectConfig: &vertex.AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs{
EnablePrivateServiceConnect: pulumi.Bool(false),
ProjectAllowlists: pulumi.StringArray{
pulumi.String("string"),
},
},
PublicEndpointDomainName: pulumi.String("string"),
ServiceAttachment: pulumi.String("string"),
},
ForceDestroy: pulumi.Bool(false),
Labels: pulumi.StringMap{
"string": pulumi.String("string"),
},
Name: pulumi.String("string"),
Optimized: &vertex.AiFeatureOnlineStoreOptimizedArgs{},
Project: pulumi.String("string"),
Region: pulumi.String("string"),
})
var aiFeatureOnlineStoreResource = new AiFeatureOnlineStore("aiFeatureOnlineStoreResource", AiFeatureOnlineStoreArgs.builder()
.bigtable(AiFeatureOnlineStoreBigtableArgs.builder()
.autoScaling(AiFeatureOnlineStoreBigtableAutoScalingArgs.builder()
.maxNodeCount(0)
.minNodeCount(0)
.cpuUtilizationTarget(0)
.build())
.build())
.dedicatedServingEndpoint(AiFeatureOnlineStoreDedicatedServingEndpointArgs.builder()
.privateServiceConnectConfig(AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs.builder()
.enablePrivateServiceConnect(false)
.projectAllowlists("string")
.build())
.publicEndpointDomainName("string")
.serviceAttachment("string")
.build())
.forceDestroy(false)
.labels(Map.of("string", "string"))
.name("string")
.optimized()
.project("string")
.region("string")
.build());
ai_feature_online_store_resource = gcp.vertex.AiFeatureOnlineStore("aiFeatureOnlineStoreResource",
bigtable={
"auto_scaling": {
"max_node_count": 0,
"min_node_count": 0,
"cpu_utilization_target": 0,
},
},
dedicated_serving_endpoint={
"private_service_connect_config": {
"enable_private_service_connect": False,
"project_allowlists": ["string"],
},
"public_endpoint_domain_name": "string",
"service_attachment": "string",
},
force_destroy=False,
labels={
"string": "string",
},
name="string",
optimized={},
project="string",
region="string")
const aiFeatureOnlineStoreResource = new gcp.vertex.AiFeatureOnlineStore("aiFeatureOnlineStoreResource", {
bigtable: {
autoScaling: {
maxNodeCount: 0,
minNodeCount: 0,
cpuUtilizationTarget: 0,
},
},
dedicatedServingEndpoint: {
privateServiceConnectConfig: {
enablePrivateServiceConnect: false,
projectAllowlists: ["string"],
},
publicEndpointDomainName: "string",
serviceAttachment: "string",
},
forceDestroy: false,
labels: {
string: "string",
},
name: "string",
optimized: {},
project: "string",
region: "string",
});
type: gcp:vertex:AiFeatureOnlineStore
properties:
bigtable:
autoScaling:
cpuUtilizationTarget: 0
maxNodeCount: 0
minNodeCount: 0
dedicatedServingEndpoint:
privateServiceConnectConfig:
enablePrivateServiceConnect: false
projectAllowlists:
- string
publicEndpointDomainName: string
serviceAttachment: string
forceDestroy: false
labels:
string: string
name: string
optimized: {}
project: string
region: string
AiFeatureOnlineStore Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.
The AiFeatureOnlineStore resource accepts the following input properties:
- Bigtable
Ai
Feature Online Store Bigtable - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- Dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- Embedding
Management AiFeature Online Store Embedding Management The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- Force
Destroy bool - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- Labels Dictionary<string, string>
- 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. - Name string
- 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.
- Optimized
Ai
Feature Online Store Optimized - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- 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 feature online store. eg us-central1
- Bigtable
Ai
Feature Online Store Bigtable Args - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- Dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint Args - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- Embedding
Management AiFeature Online Store Embedding Management Args The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- Force
Destroy bool - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- Labels map[string]string
- 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. - Name string
- 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.
- Optimized
Ai
Feature Online Store Optimized Args - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- 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 feature online store. eg us-central1
- bigtable
Ai
Feature Online Store Bigtable - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- embedding
Management AiFeature Online Store Embedding Management The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- force
Destroy Boolean - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels Map<String,String>
- 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. - name String
- 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.
- optimized
Ai
Feature Online Store Optimized - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- 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 feature online store. eg us-central1
- bigtable
Ai
Feature Online Store Bigtable - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- embedding
Management AiFeature Online Store Embedding Management The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- force
Destroy boolean - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels {[key: string]: string}
- 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. - name string
- 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.
- optimized
Ai
Feature Online Store Optimized - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- 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 feature online store. eg us-central1
- bigtable
Ai
Feature Online Store Bigtable Args - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- dedicated_
serving_ Aiendpoint Feature Online Store Dedicated Serving Endpoint Args - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- embedding_
management AiFeature Online Store Embedding Management Args The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- force_
destroy bool - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels Mapping[str, str]
- 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. - name str
- 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.
- optimized
Ai
Feature Online Store Optimized Args - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- 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 feature online store. eg us-central1
- bigtable Property Map
- Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- dedicated
Serving Property MapEndpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- embedding
Management Property Map The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- force
Destroy Boolean - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels Map<String>
- 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. - name String
- 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.
- optimized Property Map
- Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- 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 feature online store. eg us-central1
Outputs
All input properties are implicitly available as output properties. Additionally, the AiFeatureOnlineStore resource produces the following output properties:
- Create
Time string - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Effective
Labels Dictionary<string, string> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Etag string
- Used to perform consistent read-modify-write updates.
- Id string
- The provider-assigned unique ID for this managed resource.
- Pulumi
Labels Dictionary<string, string> - The combination of labels configured directly on the resource and default labels configured on the provider.
- State string
- The state of the Feature Online Store. See the possible states in this link.
- Update
Time string - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Create
Time string - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Effective
Labels map[string]string - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Etag string
- Used to perform consistent read-modify-write updates.
- Id string
- The provider-assigned unique ID for this managed resource.
- Pulumi
Labels map[string]string - The combination of labels configured directly on the resource and default labels configured on the provider.
- State string
- The state of the Feature Online Store. See the possible states in this link.
- Update
Time string - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time String - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective
Labels Map<String,String> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag String
- Used to perform consistent read-modify-write updates.
- id String
- The provider-assigned unique ID for this managed resource.
- pulumi
Labels Map<String,String> - The combination of labels configured directly on the resource and default labels configured on the provider.
- state String
- The state of the Feature Online Store. See the possible states in this link.
- update
Time String - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time string - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective
Labels {[key: string]: string} - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag string
- Used to perform consistent read-modify-write updates.
- id string
- The provider-assigned unique ID for this managed resource.
- pulumi
Labels {[key: string]: string} - The combination of labels configured directly on the resource and default labels configured on the provider.
- state string
- The state of the Feature Online Store. See the possible states in this link.
- update
Time string - The timestamp of when the feature online store 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 feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective_
labels Mapping[str, str] - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag str
- Used to perform consistent read-modify-write updates.
- id str
- The provider-assigned unique ID for this managed resource.
- pulumi_
labels Mapping[str, str] - The combination of labels configured directly on the resource and default labels configured on the provider.
- state str
- The state of the Feature Online Store. See the possible states in this link.
- update_
time str - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time String - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective
Labels Map<String> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- etag String
- Used to perform consistent read-modify-write updates.
- id String
- The provider-assigned unique ID for this managed resource.
- pulumi
Labels Map<String> - The combination of labels configured directly on the resource and default labels configured on the provider.
- state String
- The state of the Feature Online Store. See the possible states in this link.
- update
Time String - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Look up Existing AiFeatureOnlineStore Resource
Get an existing AiFeatureOnlineStore 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?: AiFeatureOnlineStoreState, opts?: CustomResourceOptions): AiFeatureOnlineStore
@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
bigtable: Optional[AiFeatureOnlineStoreBigtableArgs] = None,
create_time: Optional[str] = None,
dedicated_serving_endpoint: Optional[AiFeatureOnlineStoreDedicatedServingEndpointArgs] = None,
effective_labels: Optional[Mapping[str, str]] = None,
embedding_management: Optional[AiFeatureOnlineStoreEmbeddingManagementArgs] = None,
etag: Optional[str] = None,
force_destroy: Optional[bool] = None,
labels: Optional[Mapping[str, str]] = None,
name: Optional[str] = None,
optimized: Optional[AiFeatureOnlineStoreOptimizedArgs] = None,
project: Optional[str] = None,
pulumi_labels: Optional[Mapping[str, str]] = None,
region: Optional[str] = None,
state: Optional[str] = None,
update_time: Optional[str] = None) -> AiFeatureOnlineStore
func GetAiFeatureOnlineStore(ctx *Context, name string, id IDInput, state *AiFeatureOnlineStoreState, opts ...ResourceOption) (*AiFeatureOnlineStore, error)
public static AiFeatureOnlineStore Get(string name, Input<string> id, AiFeatureOnlineStoreState? state, CustomResourceOptions? opts = null)
public static AiFeatureOnlineStore get(String name, Output<String> id, AiFeatureOnlineStoreState 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.
- Bigtable
Ai
Feature Online Store Bigtable - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- Create
Time string - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- Effective
Labels Dictionary<string, string> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Embedding
Management AiFeature Online Store Embedding Management The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- Etag string
- Used to perform consistent read-modify-write updates.
- Force
Destroy bool - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- Labels Dictionary<string, string>
- 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. - Name string
- 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.
- Optimized
Ai
Feature Online Store Optimized - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- Pulumi
Labels Dictionary<string, string> - The combination of labels configured directly on the resource and default labels configured on the provider.
- Region string
- The region of feature online store. eg us-central1
- State string
- The state of the Feature Online Store. See the possible states in this link.
- Update
Time string - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Bigtable
Ai
Feature Online Store Bigtable Args - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- Create
Time string - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint Args - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- Effective
Labels map[string]string - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- Embedding
Management AiFeature Online Store Embedding Management Args The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- Etag string
- Used to perform consistent read-modify-write updates.
- Force
Destroy bool - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- Labels map[string]string
- 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. - Name string
- 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.
- Optimized
Ai
Feature Online Store Optimized Args - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- Pulumi
Labels map[string]string - The combination of labels configured directly on the resource and default labels configured on the provider.
- Region string
- The region of feature online store. eg us-central1
- State string
- The state of the Feature Online Store. See the possible states in this link.
- Update
Time string - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigtable
Ai
Feature Online Store Bigtable - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- create
Time String - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- effective
Labels Map<String,String> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- embedding
Management AiFeature Online Store Embedding Management The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- etag String
- Used to perform consistent read-modify-write updates.
- force
Destroy Boolean - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels Map<String,String>
- 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. - name String
- 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.
- optimized
Ai
Feature Online Store Optimized - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumi
Labels Map<String,String> - The combination of labels configured directly on the resource and default labels configured on the provider.
- region String
- The region of feature online store. eg us-central1
- state String
- The state of the Feature Online Store. See the possible states in this link.
- update
Time String - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigtable
Ai
Feature Online Store Bigtable - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- create
Time string - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- dedicated
Serving AiEndpoint Feature Online Store Dedicated Serving Endpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- effective
Labels {[key: string]: string} - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- embedding
Management AiFeature Online Store Embedding Management The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- etag string
- Used to perform consistent read-modify-write updates.
- force
Destroy boolean - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels {[key: string]: string}
- 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. - name string
- 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.
- optimized
Ai
Feature Online Store Optimized - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumi
Labels {[key: string]: string} - The combination of labels configured directly on the resource and default labels configured on the provider.
- region string
- The region of feature online store. eg us-central1
- state string
- The state of the Feature Online Store. See the possible states in this link.
- update
Time string - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigtable
Ai
Feature Online Store Bigtable Args - Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- create_
time str - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- dedicated_
serving_ Aiendpoint Feature Online Store Dedicated Serving Endpoint Args - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- effective_
labels Mapping[str, str] - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- embedding_
management AiFeature Online Store Embedding Management Args The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- etag str
- Used to perform consistent read-modify-write updates.
- force_
destroy bool - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels Mapping[str, str]
- 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. - name str
- 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.
- optimized
Ai
Feature Online Store Optimized Args - Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- project str
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumi_
labels Mapping[str, str] - The combination of labels configured directly on the resource and default labels configured on the provider.
- region str
- The region of feature online store. eg us-central1
- state str
- The state of the Feature Online Store. See the possible states in this link.
- update_
time str - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- bigtable Property Map
- Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Structure is documented below.
- create
Time String - The timestamp of when the feature online store was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- dedicated
Serving Property MapEndpoint - The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default. Structure is documented below.
- effective
Labels Map<String> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- embedding
Management Property Map The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Structure is documented below.
Warning:
embedding_management
is deprecated. This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type- etag String
- Used to perform consistent read-modify-write updates.
- force
Destroy Boolean - If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted.
- labels Map<String>
- 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. - name String
- 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.
- optimized Property Map
- Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- pulumi
Labels Map<String> - The combination of labels configured directly on the resource and default labels configured on the provider.
- region String
- The region of feature online store. eg us-central1
- state String
- The state of the Feature Online Store. See the possible states in this link.
- update
Time String - The timestamp of when the feature online store was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Supporting Types
AiFeatureOnlineStoreBigtable, AiFeatureOnlineStoreBigtableArgs
- Auto
Scaling AiFeature Online Store Bigtable Auto Scaling - Autoscaling config applied to Bigtable Instance. Structure is documented below.
- Auto
Scaling AiFeature Online Store Bigtable Auto Scaling - Autoscaling config applied to Bigtable Instance. Structure is documented below.
- auto
Scaling AiFeature Online Store Bigtable Auto Scaling - Autoscaling config applied to Bigtable Instance. Structure is documented below.
- auto
Scaling AiFeature Online Store Bigtable Auto Scaling - Autoscaling config applied to Bigtable Instance. Structure is documented below.
- auto_
scaling AiFeature Online Store Bigtable Auto Scaling - Autoscaling config applied to Bigtable Instance. Structure is documented below.
- auto
Scaling Property Map - Autoscaling config applied to Bigtable Instance. Structure is documented below.
AiFeatureOnlineStoreBigtableAutoScaling, AiFeatureOnlineStoreBigtableAutoScalingArgs
- Max
Node intCount - The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- Min
Node intCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- Cpu
Utilization intTarget - A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
- Max
Node intCount - The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- Min
Node intCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- Cpu
Utilization intTarget - A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
- max
Node IntegerCount - The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min
Node IntegerCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- cpu
Utilization IntegerTarget - A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
- max
Node numberCount - The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min
Node numberCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- cpu
Utilization numberTarget - A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
- max_
node_ intcount - The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min_
node_ intcount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- cpu_
utilization_ inttarget - A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
- max
Node NumberCount - The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min
Node NumberCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- cpu
Utilization NumberTarget - A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
AiFeatureOnlineStoreDedicatedServingEndpoint, AiFeatureOnlineStoreDedicatedServingEndpointArgs
- Private
Service AiConnect Config Feature Online Store Dedicated Serving Endpoint Private Service Connect Config - Private service connect config. Structure is documented below.
- Public
Endpoint stringDomain Name - (Output) Domain name to use for this FeatureOnlineStore
- Service
Attachment string - (Output) Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
- Private
Service AiConnect Config Feature Online Store Dedicated Serving Endpoint Private Service Connect Config - Private service connect config. Structure is documented below.
- Public
Endpoint stringDomain Name - (Output) Domain name to use for this FeatureOnlineStore
- Service
Attachment string - (Output) Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
- private
Service AiConnect Config Feature Online Store Dedicated Serving Endpoint Private Service Connect Config - Private service connect config. Structure is documented below.
- public
Endpoint StringDomain Name - (Output) Domain name to use for this FeatureOnlineStore
- service
Attachment String - (Output) Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
- private
Service AiConnect Config Feature Online Store Dedicated Serving Endpoint Private Service Connect Config - Private service connect config. Structure is documented below.
- public
Endpoint stringDomain Name - (Output) Domain name to use for this FeatureOnlineStore
- service
Attachment string - (Output) Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
- private_
service_ Aiconnect_ config Feature Online Store Dedicated Serving Endpoint Private Service Connect Config - Private service connect config. Structure is documented below.
- public_
endpoint_ strdomain_ name - (Output) Domain name to use for this FeatureOnlineStore
- service_
attachment str - (Output) Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
- private
Service Property MapConnect Config - Private service connect config. Structure is documented below.
- public
Endpoint StringDomain Name - (Output) Domain name to use for this FeatureOnlineStore
- service
Attachment String - (Output) Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfig, AiFeatureOnlineStoreDedicatedServingEndpointPrivateServiceConnectConfigArgs
- Enable
Private boolService Connect - If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.
- Project
Allowlists List<string> - A list of Projects from which the forwarding rule will target the service attachment.
- Enable
Private boolService Connect - If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.
- Project
Allowlists []string - A list of Projects from which the forwarding rule will target the service attachment.
- enable
Private BooleanService Connect - If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.
- project
Allowlists List<String> - A list of Projects from which the forwarding rule will target the service attachment.
- enable
Private booleanService Connect - If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.
- project
Allowlists string[] - A list of Projects from which the forwarding rule will target the service attachment.
- enable_
private_ boolservice_ connect - If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.
- project_
allowlists Sequence[str] - A list of Projects from which the forwarding rule will target the service attachment.
- enable
Private BooleanService Connect - If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint.
- project
Allowlists List<String> - A list of Projects from which the forwarding rule will target the service attachment.
AiFeatureOnlineStoreEmbeddingManagement, AiFeatureOnlineStoreEmbeddingManagementArgs
- Enabled bool
- Enable embedding management.
- Enabled bool
- Enable embedding management.
- enabled Boolean
- Enable embedding management.
- enabled boolean
- Enable embedding management.
- enabled bool
- Enable embedding management.
- enabled Boolean
- Enable embedding management.
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:
$ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default projects/{{project}}/locations/{{region}}/featureOnlineStores/{{name}}
$ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default {{project}}/{{region}}/{{name}}
$ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default {{region}}/{{name}}
$ pulumi import gcp:vertex/aiFeatureOnlineStore:AiFeatureOnlineStore default {{name}}
To learn more about importing existing cloud resources, see Importing resources.
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.