pulumi-gcp-kotlin/com.pulumi.gcp.vertex.kotlin/AiFeatureStore

AiFeatureStore

class AiFeatureStore : KotlinCustomResource

A collection of DataItems and Annotations on them. To get more information about Featurestore, see:

Example Usage

Vertex Ai Featurestore

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEncryptionSpecArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }
    public static void stack(Context ctx) {
        var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()
            .encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .forceDestroy(true)
            .labels(Map.of("foo", "bar"))
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .fixedNodeCount(2)
                .build())
            .region("us-central1")
            .build());
    }
}
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Vertex Ai Featurestore With Beta Fields

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEncryptionSpecArgs;
import com.pulumi.resources.CustomResourceOptions;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }
    public static void stack(Context ctx) {
        var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()
            .labels(Map.of("foo", "bar"))
            .region("us-central1")
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .fixedNodeCount(2)
                .build())
            .encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .onlineStorageTtlDays(30)
            .forceDestroy(true)
            .build(), CustomResourceOptions.builder()
                .provider(google_beta)
                .build());
    }
}
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Vertex Ai Featurestore Scaling

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureStore;
import com.pulumi.gcp.vertex.AiFeatureStoreArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreEncryptionSpecArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigArgs;
import com.pulumi.gcp.vertex.inputs.AiFeatureStoreOnlineServingConfigScalingArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;
public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }
    public static void stack(Context ctx) {
        var featurestore = new AiFeatureStore("featurestore", AiFeatureStoreArgs.builder()
            .encryptionSpec(AiFeatureStoreEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .forceDestroy(true)
            .labels(Map.of("foo", "bar"))
            .onlineServingConfig(AiFeatureStoreOnlineServingConfigArgs.builder()
                .scaling(AiFeatureStoreOnlineServingConfigScalingArgs.builder()
                    .maxNodeCount(10)
                    .minNodeCount(2)
                    .build())
                .build())
            .region("us-central1")
            .build());
    }
}
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Import

Featurestore can be imported using any of these accepted formats

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

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val createTime: Output<String>

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

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val encryptionSpec: Output<AiFeatureStoreEncryptionSpec>?

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

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val etag: Output<String>

Used to perform consistent read-modify-write updates.

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val forceDestroy: Output<Boolean>?

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

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val id: Output<String>
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val labels: Output<Map<String, String>>?

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

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val name: Output<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.

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val onlineServingConfig: Output<AiFeatureStoreOnlineServingConfig>?

Config for online serving resources. Structure is documented below.

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val onlineStorageTtlDays: Output<Int>?

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

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val project: Output<String>

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

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val pulumiChildResources: Set<KotlinResource>
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val region: Output<String>

The region of the dataset. eg us-central1

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val updateTime: Output<String>

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

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val urn: Output<String>