AiEndpointArgs

data class AiEndpointArgs(val description: Output<String>? = null, val displayName: Output<String>? = null, val encryptionSpec: Output<AiEndpointEncryptionSpecArgs>? = null, val labels: Output<Map<String, String>>? = null, val location: Output<String>? = null, val name: Output<String>? = null, val network: Output<String>? = null, val project: Output<String>? = null, val region: Output<String>? = null) : ConvertibleToJava<AiEndpointArgs>

Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations. To get more information about Endpoint, see:

Example Usage

Vertex Ai Endpoint Network

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.compute.ComputeFunctions;
import com.pulumi.gcp.compute.inputs.GetNetworkArgs;
import com.pulumi.gcp.compute.GlobalAddress;
import com.pulumi.gcp.compute.GlobalAddressArgs;
import com.pulumi.gcp.servicenetworking.Connection;
import com.pulumi.gcp.servicenetworking.ConnectionArgs;
import com.pulumi.gcp.organizations.OrganizationsFunctions;
import com.pulumi.gcp.organizations.inputs.GetProjectArgs;
import com.pulumi.gcp.vertex.AiEndpoint;
import com.pulumi.gcp.vertex.AiEndpointArgs;
import com.pulumi.gcp.vertex.inputs.AiEndpointEncryptionSpecArgs;
import com.pulumi.gcp.kms.CryptoKeyIAMMember;
import com.pulumi.gcp.kms.CryptoKeyIAMMemberArgs;
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) {
final var vertexNetwork = ComputeFunctions.getNetwork(GetNetworkArgs.builder()
.name("network-name")
.build());
var vertexRange = new GlobalAddress("vertexRange", GlobalAddressArgs.builder()
.purpose("VPC_PEERING")
.addressType("INTERNAL")
.prefixLength(24)
.network(vertexNetwork.applyValue(getNetworkResult -> getNetworkResult.id()))
.build());
var vertexVpcConnection = new Connection("vertexVpcConnection", ConnectionArgs.builder()
.network(vertexNetwork.applyValue(getNetworkResult -> getNetworkResult.id()))
.service("servicenetworking.googleapis.com")
.reservedPeeringRanges(vertexRange.name())
.build());
final var project = OrganizationsFunctions.getProject();
var endpoint = new AiEndpoint("endpoint", AiEndpointArgs.builder()
.displayName("sample-endpoint")
.description("A sample vertex endpoint")
.location("us-central1")
.region("us-central1")
.labels(Map.of("label-one", "value-one"))
.network(String.format("projects/%s/global/networks/%s", project.applyValue(getProjectResult -> getProjectResult.number()),vertexNetwork.applyValue(getNetworkResult -> getNetworkResult.name())))
.encryptionSpec(AiEndpointEncryptionSpecArgs.builder()
.kmsKeyName("kms-name")
.build())
.build(), CustomResourceOptions.builder()
.dependsOn(vertexVpcConnection)
.build());
var cryptoKey = new CryptoKeyIAMMember("cryptoKey", CryptoKeyIAMMemberArgs.builder()
.cryptoKeyId("kms-name")
.role("roles/cloudkms.cryptoKeyEncrypterDecrypter")
.member(String.format("serviceAccount:service-%s@gcp-sa-aiplatform.iam.gserviceaccount.com", project.applyValue(getProjectResult -> getProjectResult.number())))
.build());
}
}

Import

Endpoint can be imported using any of these accepted formats

$ pulumi import gcp:vertex/aiEndpoint:AiEndpoint default projects/{{project}}/locations/{{location}}/endpoints/{{name}}
$ pulumi import gcp:vertex/aiEndpoint:AiEndpoint default {{project}}/{{location}}/{{name}}
$ pulumi import gcp:vertex/aiEndpoint:AiEndpoint default {{location}}/{{name}}

Constructors

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constructor(description: Output<String>? = null, displayName: Output<String>? = null, encryptionSpec: Output<AiEndpointEncryptionSpecArgs>? = null, labels: Output<Map<String, String>>? = null, location: Output<String>? = null, name: Output<String>? = null, network: Output<String>? = null, project: Output<String>? = null, region: Output<String>? = null)

Properties

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val description: Output<String>? = null

The description of the Endpoint.

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val displayName: Output<String>? = null

Required. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.

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Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key. Structure is documented below.

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val labels: Output<Map<String, String>>? = null

The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels.

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val location: Output<String>? = null

The location for the resource

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val name: Output<String>? = null

The resource name of the Endpoint. The name must be numeric with no leading zeros and can be at most 10 digits.

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val network: Output<String>? = null

The full name of the Google Compute Engine network to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. Format: projects/{project}/global/networks/{network}. Where {project} is a project number, as in 12345, and {network} is network name.

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val project: Output<String>? = null

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 region: Output<String>? = null

The region for the resource

Functions

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open override fun toJava(): AiEndpointArgs