gcp.vertex.AiFeatureStore
Explore with Pulumi AI
A collection of DataItems and Annotations on them.
To get more information about Featurestore, see:
- API documentation
- How-to Guides
Example Usage
Vertex Ai Featurestore
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
name: "terraform",
labels: {
foo: "bar",
},
region: "us-central1",
onlineServingConfig: {
fixedNodeCount: 2,
},
encryptionSpec: {
kmsKeyName: "kms-name",
},
forceDestroy: true,
});
import pulumi
import pulumi_gcp as gcp
featurestore = gcp.vertex.AiFeatureStore("featurestore",
name="terraform",
labels={
"foo": "bar",
},
region="us-central1",
online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
fixed_node_count=2,
),
encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
kms_key_name="kms-name",
),
force_destroy=True)
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.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
Name: pulumi.String("terraform"),
Labels: pulumi.StringMap{
"foo": pulumi.String("bar"),
},
Region: pulumi.String("us-central1"),
OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
FixedNodeCount: pulumi.Int(2),
},
EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
KmsKeyName: pulumi.String("kms-name"),
},
ForceDestroy: pulumi.Bool(true),
})
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 featurestore = new Gcp.Vertex.AiFeatureStore("featurestore", new()
{
Name = "terraform",
Labels =
{
{ "foo", "bar" },
},
Region = "us-central1",
OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
{
FixedNodeCount = 2,
},
EncryptionSpec = new Gcp.Vertex.Inputs.AiFeatureStoreEncryptionSpecArgs
{
KmsKeyName = "kms-name",
},
ForceDestroy = true,
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEncryptionSpecArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()
.name("terraform")
.labels(Map.of("foo", "bar"))
.region("us-central1")
.onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
.fixedNodeCount(2)
.build())
.encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
.kmsKeyName("kms-name")
.build())
.forceDestroy(true)
.build());
}
}
resources:
featurestore:
type: gcp:vertex:AiFeatureStore
properties:
name: terraform
labels:
foo: bar
region: us-central1
onlineServingConfig:
fixedNodeCount: 2
encryptionSpec:
kmsKeyName: kms-name
forceDestroy: true
Vertex Ai Featurestore With Beta Fields
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
name: "terraform2",
labels: {
foo: "bar",
},
region: "us-central1",
onlineServingConfig: {
fixedNodeCount: 2,
},
encryptionSpec: {
kmsKeyName: "kms-name",
},
onlineStorageTtlDays: 30,
forceDestroy: true,
});
import pulumi
import pulumi_gcp as gcp
featurestore = gcp.vertex.AiFeatureStore("featurestore",
name="terraform2",
labels={
"foo": "bar",
},
region="us-central1",
online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
fixed_node_count=2,
),
encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
kms_key_name="kms-name",
),
online_storage_ttl_days=30,
force_destroy=True)
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.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
Name: pulumi.String("terraform2"),
Labels: pulumi.StringMap{
"foo": pulumi.String("bar"),
},
Region: pulumi.String("us-central1"),
OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
FixedNodeCount: pulumi.Int(2),
},
EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
KmsKeyName: pulumi.String("kms-name"),
},
OnlineStorageTtlDays: pulumi.Int(30),
ForceDestroy: pulumi.Bool(true),
})
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 featurestore = new Gcp.Vertex.AiFeatureStore("featurestore", new()
{
Name = "terraform2",
Labels =
{
{ "foo", "bar" },
},
Region = "us-central1",
OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
{
FixedNodeCount = 2,
},
EncryptionSpec = new Gcp.Vertex.Inputs.AiFeatureStoreEncryptionSpecArgs
{
KmsKeyName = "kms-name",
},
OnlineStorageTtlDays = 30,
ForceDestroy = true,
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEncryptionSpecArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()
.name("terraform2")
.labels(Map.of("foo", "bar"))
.region("us-central1")
.onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
.fixedNodeCount(2)
.build())
.encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
.kmsKeyName("kms-name")
.build())
.onlineStorageTtlDays(30)
.forceDestroy(true)
.build());
}
}
resources:
featurestore:
type: gcp:vertex:AiFeatureStore
properties:
name: terraform2
labels:
foo: bar
region: us-central1
onlineServingConfig:
fixedNodeCount: 2
encryptionSpec:
kmsKeyName: kms-name
onlineStorageTtlDays: 30
forceDestroy: true
Vertex Ai Featurestore Scaling
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";
const featurestore = new gcp.vertex.AiFeatureStore("featurestore", {
name: "terraform3",
labels: {
foo: "bar",
},
region: "us-central1",
onlineServingConfig: {
scaling: {
minNodeCount: 2,
maxNodeCount: 10,
},
},
encryptionSpec: {
kmsKeyName: "kms-name",
},
forceDestroy: true,
});
import pulumi
import pulumi_gcp as gcp
featurestore = gcp.vertex.AiFeatureStore("featurestore",
name="terraform3",
labels={
"foo": "bar",
},
region="us-central1",
online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
scaling=gcp.vertex.AiFeatureStoreOnlineServingConfigScalingArgs(
min_node_count=2,
max_node_count=10,
),
),
encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
kms_key_name="kms-name",
),
force_destroy=True)
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.NewAiFeatureStore(ctx, "featurestore", &vertex.AiFeatureStoreArgs{
Name: pulumi.String("terraform3"),
Labels: pulumi.StringMap{
"foo": pulumi.String("bar"),
},
Region: pulumi.String("us-central1"),
OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
Scaling: &vertex.AiFeatureStoreOnlineServingConfigScalingArgs{
MinNodeCount: pulumi.Int(2),
MaxNodeCount: pulumi.Int(10),
},
},
EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
KmsKeyName: pulumi.String("kms-name"),
},
ForceDestroy: pulumi.Bool(true),
})
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 featurestore = new Gcp.Vertex.AiFeatureStore("featurestore", new()
{
Name = "terraform3",
Labels =
{
{ "foo", "bar" },
},
Region = "us-central1",
OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
{
Scaling = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigScalingArgs
{
MinNodeCount = 2,
MaxNodeCount = 10,
},
},
EncryptionSpec = new Gcp.Vertex.Inputs.AiFeatureStoreEncryptionSpecArgs
{
KmsKeyName = "kms-name",
},
ForceDestroy = true,
});
});
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigScalingArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEncryptionSpecArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
public static void main(String[] args) {
Pulumi.run(App::stack);
}
public static void stack(Context ctx) {
var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()
.name("terraform3")
.labels(Map.of("foo", "bar"))
.region("us-central1")
.onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
.scaling(AiFeatureStoreOnlineServingConfigScalingArgs.builder()
.minNodeCount(2)
.maxNodeCount(10)
.build())
.build())
.encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
.kmsKeyName("kms-name")
.build())
.forceDestroy(true)
.build());
}
}
resources:
featurestore:
type: gcp:vertex:AiFeatureStore
properties:
name: terraform3
labels:
foo: bar
region: us-central1
onlineServingConfig:
scaling:
minNodeCount: 2
maxNodeCount: 10
encryptionSpec:
kmsKeyName: kms-name
forceDestroy: true
Create AiFeatureStore Resource
Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.
Constructor syntax
new AiFeatureStore(name: string, args?: AiFeatureStoreArgs, opts?: CustomResourceOptions);
@overload
def AiFeatureStore(resource_name: str,
args: Optional[AiFeatureStoreArgs] = None,
opts: Optional[ResourceOptions] = None)
@overload
def AiFeatureStore(resource_name: str,
opts: Optional[ResourceOptions] = None,
encryption_spec: Optional[AiFeatureStoreEncryptionSpecArgs] = None,
force_destroy: Optional[bool] = None,
labels: Optional[Mapping[str, str]] = None,
name: Optional[str] = None,
online_serving_config: Optional[AiFeatureStoreOnlineServingConfigArgs] = None,
online_storage_ttl_days: Optional[int] = None,
project: Optional[str] = None,
region: Optional[str] = None)
func NewAiFeatureStore(ctx *Context, name string, args *AiFeatureStoreArgs, opts ...ResourceOption) (*AiFeatureStore, error)
public AiFeatureStore(string name, AiFeatureStoreArgs? args = null, CustomResourceOptions? opts = null)
public AiFeatureStore(String name, AiFeatureStoreArgs args)
public AiFeatureStore(String name, AiFeatureStoreArgs args, CustomResourceOptions options)
type: gcp:vertex:AiFeatureStore
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.
Parameters
- name string
- The unique name of the resource.
- args AiFeatureStoreArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- resource_name str
- The unique name of the resource.
- args AiFeatureStoreArgs
- The arguments to resource properties.
- opts ResourceOptions
- Bag of options to control resource's behavior.
- ctx Context
- Context object for the current deployment.
- name string
- The unique name of the resource.
- args AiFeatureStoreArgs
- The arguments to resource properties.
- opts ResourceOption
- Bag of options to control resource's behavior.
- name string
- The unique name of the resource.
- args AiFeatureStoreArgs
- The arguments to resource properties.
- opts CustomResourceOptions
- Bag of options to control resource's behavior.
- name String
- The unique name of the resource.
- args AiFeatureStoreArgs
- The arguments to resource properties.
- options CustomResourceOptions
- Bag of options to control resource's behavior.
Constructor example
The following reference example uses placeholder values for all input properties.
var aiFeatureStoreResource = new Gcp.Vertex.AiFeatureStore("aiFeatureStoreResource", new()
{
EncryptionSpec = new Gcp.Vertex.Inputs.AiFeatureStoreEncryptionSpecArgs
{
KmsKeyName = "string",
},
ForceDestroy = false,
Labels =
{
{ "string", "string" },
},
Name = "string",
OnlineServingConfig = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigArgs
{
FixedNodeCount = 0,
Scaling = new Gcp.Vertex.Inputs.AiFeatureStoreOnlineServingConfigScalingArgs
{
MaxNodeCount = 0,
MinNodeCount = 0,
},
},
OnlineStorageTtlDays = 0,
Project = "string",
Region = "string",
});
example, err := vertex.NewAiFeatureStore(ctx, "aiFeatureStoreResource", &vertex.AiFeatureStoreArgs{
EncryptionSpec: &vertex.AiFeatureStoreEncryptionSpecArgs{
KmsKeyName: pulumi.String("string"),
},
ForceDestroy: pulumi.Bool(false),
Labels: pulumi.StringMap{
"string": pulumi.String("string"),
},
Name: pulumi.String("string"),
OnlineServingConfig: &vertex.AiFeatureStoreOnlineServingConfigArgs{
FixedNodeCount: pulumi.Int(0),
Scaling: &vertex.AiFeatureStoreOnlineServingConfigScalingArgs{
MaxNodeCount: pulumi.Int(0),
MinNodeCount: pulumi.Int(0),
},
},
OnlineStorageTtlDays: pulumi.Int(0),
Project: pulumi.String("string"),
Region: pulumi.String("string"),
})
var aiFeatureStoreResource = new AiFeatureStore("aiFeatureStoreResource", AiFeatureStoreArgs.builder()
.encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
.kmsKeyName("string")
.build())
.forceDestroy(false)
.labels(Map.of("string", "string"))
.name("string")
.onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
.fixedNodeCount(0)
.scaling(AiFeatureStoreOnlineServingConfigScalingArgs.builder()
.maxNodeCount(0)
.minNodeCount(0)
.build())
.build())
.onlineStorageTtlDays(0)
.project("string")
.region("string")
.build());
ai_feature_store_resource = gcp.vertex.AiFeatureStore("aiFeatureStoreResource",
encryption_spec=gcp.vertex.AiFeatureStoreEncryptionSpecArgs(
kms_key_name="string",
),
force_destroy=False,
labels={
"string": "string",
},
name="string",
online_serving_config=gcp.vertex.AiFeatureStoreOnlineServingConfigArgs(
fixed_node_count=0,
scaling=gcp.vertex.AiFeatureStoreOnlineServingConfigScalingArgs(
max_node_count=0,
min_node_count=0,
),
),
online_storage_ttl_days=0,
project="string",
region="string")
const aiFeatureStoreResource = new gcp.vertex.AiFeatureStore("aiFeatureStoreResource", {
encryptionSpec: {
kmsKeyName: "string",
},
forceDestroy: false,
labels: {
string: "string",
},
name: "string",
onlineServingConfig: {
fixedNodeCount: 0,
scaling: {
maxNodeCount: 0,
minNodeCount: 0,
},
},
onlineStorageTtlDays: 0,
project: "string",
region: "string",
});
type: gcp:vertex:AiFeatureStore
properties:
encryptionSpec:
kmsKeyName: string
forceDestroy: false
labels:
string: string
name: string
onlineServingConfig:
fixedNodeCount: 0
scaling:
maxNodeCount: 0
minNodeCount: 0
onlineStorageTtlDays: 0
project: string
region: string
AiFeatureStore Resource Properties
To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.
Inputs
The AiFeatureStore resource accepts the following input properties:
- Encryption
Spec AiFeature Store Encryption Spec - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- Force
Destroy bool - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- Labels Dictionary<string, string>
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- Online
Serving AiConfig Feature Store Online Serving Config - Config for online serving resources. Structure is documented below.
- Online
Storage intTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- Region string
- The region of the dataset. eg us-central1
- Encryption
Spec AiFeature Store Encryption Spec Args - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- Force
Destroy bool - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- Labels map[string]string
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- Online
Serving AiConfig Feature Store Online Serving Config Args - Config for online serving resources. Structure is documented below.
- Online
Storage intTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- Region string
- The region of the dataset. eg us-central1
- encryption
Spec AiFeature Store Encryption Spec - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- force
Destroy Boolean - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels Map<String,String>
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online
Serving AiConfig Feature Store Online Serving Config - Config for online serving resources. Structure is documented below.
- online
Storage IntegerTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region String
- The region of the dataset. eg us-central1
- encryption
Spec AiFeature Store Encryption Spec - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- force
Destroy boolean - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels {[key: string]: string}
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online
Serving AiConfig Feature Store Online Serving Config - Config for online serving resources. Structure is documented below.
- online
Storage numberTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region string
- The region of the dataset. eg us-central1
- encryption_
spec AiFeature Store Encryption Spec Args - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- force_
destroy bool - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels Mapping[str, str]
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online_
serving_ Aiconfig Feature Store Online Serving Config Args - Config for online serving resources. Structure is documented below.
- online_
storage_ intttl_ days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project str
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region str
- The region of the dataset. eg us-central1
- encryption
Spec Property Map - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- force
Destroy Boolean - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels Map<String>
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online
Serving Property MapConfig - Config for online serving resources. Structure is documented below.
- online
Storage NumberTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- region String
- The region of the dataset. eg us-central1
Outputs
All input properties are implicitly available as output properties. Additionally, the AiFeatureStore resource produces the following output properties:
- Create
Time string - The timestamp of when the featurestore 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.
- Update
Time string - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Create
Time string - The timestamp of when the featurestore 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.
- Update
Time string - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time String - The timestamp of when the featurestore 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.
- update
Time String - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time string - The timestamp of when the featurestore 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.
- update
Time string - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create_
time str - The timestamp of when the featurestore was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- 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.
- update_
time str - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time String - The timestamp of when the featurestore 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.
- update
Time String - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Look up Existing AiFeatureStore Resource
Get an existing AiFeatureStore resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.
public static get(name: string, id: Input<ID>, state?: AiFeatureStoreState, opts?: CustomResourceOptions): AiFeatureStore
@staticmethod
def get(resource_name: str,
id: str,
opts: Optional[ResourceOptions] = None,
create_time: Optional[str] = None,
effective_labels: Optional[Mapping[str, str]] = None,
encryption_spec: Optional[AiFeatureStoreEncryptionSpecArgs] = None,
etag: Optional[str] = None,
force_destroy: Optional[bool] = None,
labels: Optional[Mapping[str, str]] = None,
name: Optional[str] = None,
online_serving_config: Optional[AiFeatureStoreOnlineServingConfigArgs] = None,
online_storage_ttl_days: Optional[int] = None,
project: Optional[str] = None,
pulumi_labels: Optional[Mapping[str, str]] = None,
region: Optional[str] = None,
update_time: Optional[str] = None) -> AiFeatureStore
func GetAiFeatureStore(ctx *Context, name string, id IDInput, state *AiFeatureStoreState, opts ...ResourceOption) (*AiFeatureStore, error)
public static AiFeatureStore Get(string name, Input<string> id, AiFeatureStoreState? state, CustomResourceOptions? opts = null)
public static AiFeatureStore get(String name, Output<String> id, AiFeatureStoreState state, CustomResourceOptions options)
Resource lookup is not supported in YAML
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- resource_name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- name
- The unique name of the resulting resource.
- id
- The unique provider ID of the resource to lookup.
- state
- Any extra arguments used during the lookup.
- opts
- A bag of options that control this resource's behavior.
- Create
Time string - The timestamp of when the featurestore 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.
- Encryption
Spec AiFeature Store Encryption Spec - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- Etag string
- Used to perform consistent read-modify-write updates.
- Force
Destroy bool - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- Labels Dictionary<string, string>
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- Online
Serving AiConfig Feature Store Online Serving Config - Config for online serving resources. Structure is documented below.
- Online
Storage intTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- 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 the dataset. eg us-central1
- Update
Time string - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Create
Time string - The timestamp of when the featurestore 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.
- Encryption
Spec AiFeature Store Encryption Spec Args - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- Etag string
- Used to perform consistent read-modify-write updates.
- Force
Destroy bool - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- Labels map[string]string
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- Online
Serving AiConfig Feature Store Online Serving Config Args - Config for online serving resources. Structure is documented below.
- Online
Storage intTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- Project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- 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 the dataset. eg us-central1
- Update
Time string - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time String - The timestamp of when the featurestore 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.
- encryption
Spec AiFeature Store Encryption Spec - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- etag String
- Used to perform consistent read-modify-write updates.
- force
Destroy Boolean - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels Map<String,String>
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online
Serving AiConfig Feature Store Online Serving Config - Config for online serving resources. Structure is documented below.
- online
Storage IntegerTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- 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 the dataset. eg us-central1
- update
Time String - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time string - The timestamp of when the featurestore 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.
- encryption
Spec AiFeature Store Encryption Spec - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- etag string
- Used to perform consistent read-modify-write updates.
- force
Destroy boolean - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels {[key: string]: string}
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online
Serving AiConfig Feature Store Online Serving Config - Config for online serving resources. Structure is documented below.
- online
Storage numberTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project string
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- 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 the dataset. eg us-central1
- update
Time string - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create_
time str - The timestamp of when the featurestore was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- 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.
- encryption_
spec AiFeature Store Encryption Spec Args - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- etag str
- Used to perform consistent read-modify-write updates.
- force_
destroy bool - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels Mapping[str, str]
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online_
serving_ Aiconfig Feature Store Online Serving Config Args - Config for online serving resources. Structure is documented below.
- online_
storage_ intttl_ days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project str
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- 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 the dataset. eg us-central1
- update_
time str - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- create
Time String - The timestamp of when the featurestore 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.
- encryption
Spec Property Map - If set, both of the online and offline data storage will be secured by this key. Structure is documented below.
- etag String
- Used to perform consistent read-modify-write updates.
- force
Destroy Boolean - If set to true, any EntityTypes and Features for this Featurestore will also be deleted
- labels Map<String>
A set of key/value label pairs to assign to this Featurestore.
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 name of the Featurestore. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
- online
Serving Property MapConfig - Config for online serving resources. Structure is documented below.
- online
Storage NumberTtl Days - TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days
- project String
- The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
- 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 the dataset. eg us-central1
- update
Time String - The timestamp of when the featurestore was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
Supporting Types
AiFeatureStoreEncryptionSpec, AiFeatureStoreEncryptionSpecArgs
- Kms
Key stringName - The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
- Kms
Key stringName - The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
- kms
Key StringName - The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
- kms
Key stringName - The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
- kms_
key_ strname - The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
- kms
Key StringName - The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my-key. The key needs to be in the same region as where the compute resource is created.
AiFeatureStoreOnlineServingConfig, AiFeatureStoreOnlineServingConfigArgs
- Fixed
Node intCount - The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.
- Scaling
Ai
Feature Store Online Serving Config Scaling - Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.
- Fixed
Node intCount - The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.
- Scaling
Ai
Feature Store Online Serving Config Scaling - Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.
- fixed
Node IntegerCount - The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.
- scaling
Ai
Feature Store Online Serving Config Scaling - Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.
- fixed
Node numberCount - The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.
- scaling
Ai
Feature Store Online Serving Config Scaling - Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.
- fixed_
node_ intcount - The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.
- scaling
Ai
Feature Store Online Serving Config Scaling - Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.
- fixed
Node NumberCount - The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating.
- scaling Property Map
- Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Structure is documented below.
AiFeatureStoreOnlineServingConfigScaling, AiFeatureStoreOnlineServingConfigScalingArgs
- Max
Node intCount - The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- Min
Node intCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- Max
Node intCount - The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- Min
Node intCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- max
Node IntegerCount - The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min
Node IntegerCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- max
Node numberCount - The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min
Node numberCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- max_
node_ intcount - The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min_
node_ intcount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
- max
Node NumberCount - The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of 'minNodeCount'.
- min
Node NumberCount - The minimum number of nodes to scale down to. Must be greater than or equal to 1.
Import
Featurestore can be imported using any of these accepted formats:
projects/{{project}}/locations/{{region}}/featurestores/{{name}}
{{project}}/{{region}}/{{name}}
{{region}}/{{name}}
{{name}}
When using the pulumi import
command, Featurestore can be imported using one of the formats above. For example:
$ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default projects/{{project}}/locations/{{region}}/featurestores/{{name}}
$ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default {{project}}/{{region}}/{{name}}
$ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default {{region}}/{{name}}
$ pulumi import gcp:vertex/aiFeatureStore:AiFeatureStore default {{name}}
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.