@pulumi/gcp
Version:
A Pulumi package for creating and managing Google Cloud Platform resources.
234 lines • 10.6 kB
JavaScript
;
// *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. ***
// *** Do not edit by hand unless you're certain you know what you are doing! ***
Object.defineProperty(exports, "__esModule", { value: true });
exports.AiEndpoint = void 0;
const pulumi = require("@pulumi/pulumi");
const utilities = require("../utilities");
/**
* Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.
*
* To get more information about Endpoint, see:
*
* * [API documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.endpoints)
* * How-to Guides
* * [Official Documentation](https://cloud.google.com/vertex-ai/docs)
*
* ## Example Usage
*
* ### Vertex Ai Endpoint Network
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
*
* const vertexNetwork = new gcp.compute.Network("vertex_network", {name: "network-name"});
* const vertexRange = new gcp.compute.GlobalAddress("vertex_range", {
* name: "address-name",
* purpose: "VPC_PEERING",
* addressType: "INTERNAL",
* prefixLength: 24,
* network: vertexNetwork.id,
* });
* const vertexVpcConnection = new gcp.servicenetworking.Connection("vertex_vpc_connection", {
* network: vertexNetwork.id,
* service: "servicenetworking.googleapis.com",
* reservedPeeringRanges: [vertexRange.name],
* });
* const bqDataset = new gcp.bigquery.Dataset("bq_dataset", {
* datasetId: "some_dataset",
* friendlyName: "logging dataset",
* description: "This is a dataset that requests are logged to",
* location: "US",
* deleteContentsOnDestroy: true,
* });
* const project = gcp.organizations.getProject({});
* const endpoint = new gcp.vertex.AiEndpoint("endpoint", {
* name: "endpoint-name",
* displayName: "sample-endpoint",
* description: "A sample vertex endpoint",
* location: "us-central1",
* region: "us-central1",
* labels: {
* "label-one": "value-one",
* },
* network: pulumi.all([project, vertexNetwork.name]).apply(([project, name]) => `projects/${project.number}/global/networks/${name}`),
* encryptionSpec: {
* kmsKeyName: "kms-name",
* },
* predictRequestResponseLoggingConfig: {
* bigqueryDestination: {
* outputUri: pulumi.all([project, bqDataset.datasetId]).apply(([project, datasetId]) => `bq://${project.projectId}.${datasetId}.request_response_logging`),
* },
* enabled: true,
* samplingRate: 0.1,
* },
* trafficSplit: JSON.stringify({
* "12345": 100,
* }),
* }, {
* dependsOn: [vertexVpcConnection],
* });
* const cryptoKey = new gcp.kms.CryptoKeyIAMMember("crypto_key", {
* cryptoKeyId: "kms-name",
* role: "roles/cloudkms.cryptoKeyEncrypterDecrypter",
* member: project.then(project => `serviceAccount:service-${project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com`),
* });
* ```
* ### Vertex Ai Endpoint Private Service Connect
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
*
* const project = gcp.organizations.getProject({});
* const endpoint = new gcp.vertex.AiEndpoint("endpoint", {
* name: "endpoint-name_9394",
* displayName: "sample-endpoint",
* description: "A sample vertex endpoint",
* location: "us-central1",
* region: "us-central1",
* labels: {
* "label-one": "value-one",
* },
* privateServiceConnectConfig: {
* enablePrivateServiceConnect: true,
* projectAllowlists: [project.then(project => project.projectId)],
* enableSecurePrivateServiceConnect: false,
* },
* });
* ```
* ### Vertex Ai Endpoint Dedicated Endpoint
*
* ```typescript
* import * as pulumi from "@pulumi/pulumi";
* import * as gcp from "@pulumi/gcp";
*
* const endpoint = new gcp.vertex.AiEndpoint("endpoint", {
* name: "endpoint-name_11380",
* displayName: "sample-endpoint",
* description: "A sample vertex endpoint",
* location: "us-central1",
* region: "us-central1",
* labels: {
* "label-one": "value-one",
* },
* dedicatedEndpointEnabled: true,
* });
* const project = gcp.organizations.getProject({});
* ```
*
* ## Import
*
* Endpoint can be imported using any of these accepted formats:
*
* * `projects/{{project}}/locations/{{location}}/endpoints/{{name}}`
*
* * `{{project}}/{{location}}/{{name}}`
*
* * `{{location}}/{{name}}`
*
* When using the `pulumi import` command, Endpoint can be imported using one of the formats above. For example:
*
* ```sh
* $ pulumi import gcp:vertex/aiEndpoint:AiEndpoint default projects/{{project}}/locations/{{location}}/endpoints/{{name}}
* ```
*
* ```sh
* $ pulumi import gcp:vertex/aiEndpoint:AiEndpoint default {{project}}/{{location}}/{{name}}
* ```
*
* ```sh
* $ pulumi import gcp:vertex/aiEndpoint:AiEndpoint default {{location}}/{{name}}
* ```
*/
class AiEndpoint extends pulumi.CustomResource {
/**
* Get an existing AiEndpoint resource's state with the given name, ID, and optional extra
* properties used to qualify the lookup.
*
* @param name The _unique_ name of the resulting resource.
* @param id The _unique_ provider ID of the resource to lookup.
* @param state Any extra arguments used during the lookup.
* @param opts Optional settings to control the behavior of the CustomResource.
*/
static get(name, id, state, opts) {
return new AiEndpoint(name, state, Object.assign(Object.assign({}, opts), { id: id }));
}
/**
* Returns true if the given object is an instance of AiEndpoint. This is designed to work even
* when multiple copies of the Pulumi SDK have been loaded into the same process.
*/
static isInstance(obj) {
if (obj === undefined || obj === null) {
return false;
}
return obj['__pulumiType'] === AiEndpoint.__pulumiType;
}
constructor(name, argsOrState, opts) {
let resourceInputs = {};
opts = opts || {};
if (opts.id) {
const state = argsOrState;
resourceInputs["createTime"] = state ? state.createTime : undefined;
resourceInputs["dedicatedEndpointDns"] = state ? state.dedicatedEndpointDns : undefined;
resourceInputs["dedicatedEndpointEnabled"] = state ? state.dedicatedEndpointEnabled : undefined;
resourceInputs["deployedModels"] = state ? state.deployedModels : undefined;
resourceInputs["description"] = state ? state.description : undefined;
resourceInputs["displayName"] = state ? state.displayName : undefined;
resourceInputs["effectiveLabels"] = state ? state.effectiveLabels : undefined;
resourceInputs["encryptionSpec"] = state ? state.encryptionSpec : undefined;
resourceInputs["etag"] = state ? state.etag : undefined;
resourceInputs["labels"] = state ? state.labels : undefined;
resourceInputs["location"] = state ? state.location : undefined;
resourceInputs["modelDeploymentMonitoringJob"] = state ? state.modelDeploymentMonitoringJob : undefined;
resourceInputs["name"] = state ? state.name : undefined;
resourceInputs["network"] = state ? state.network : undefined;
resourceInputs["predictRequestResponseLoggingConfig"] = state ? state.predictRequestResponseLoggingConfig : undefined;
resourceInputs["privateServiceConnectConfig"] = state ? state.privateServiceConnectConfig : undefined;
resourceInputs["project"] = state ? state.project : undefined;
resourceInputs["pulumiLabels"] = state ? state.pulumiLabels : undefined;
resourceInputs["region"] = state ? state.region : undefined;
resourceInputs["trafficSplit"] = state ? state.trafficSplit : undefined;
resourceInputs["updateTime"] = state ? state.updateTime : undefined;
}
else {
const args = argsOrState;
if ((!args || args.displayName === undefined) && !opts.urn) {
throw new Error("Missing required property 'displayName'");
}
if ((!args || args.location === undefined) && !opts.urn) {
throw new Error("Missing required property 'location'");
}
resourceInputs["dedicatedEndpointEnabled"] = args ? args.dedicatedEndpointEnabled : undefined;
resourceInputs["description"] = args ? args.description : undefined;
resourceInputs["displayName"] = args ? args.displayName : undefined;
resourceInputs["encryptionSpec"] = args ? args.encryptionSpec : undefined;
resourceInputs["labels"] = args ? args.labels : undefined;
resourceInputs["location"] = args ? args.location : undefined;
resourceInputs["name"] = args ? args.name : undefined;
resourceInputs["network"] = args ? args.network : undefined;
resourceInputs["predictRequestResponseLoggingConfig"] = args ? args.predictRequestResponseLoggingConfig : undefined;
resourceInputs["privateServiceConnectConfig"] = args ? args.privateServiceConnectConfig : undefined;
resourceInputs["project"] = args ? args.project : undefined;
resourceInputs["region"] = args ? args.region : undefined;
resourceInputs["trafficSplit"] = args ? args.trafficSplit : undefined;
resourceInputs["createTime"] = undefined /*out*/;
resourceInputs["dedicatedEndpointDns"] = undefined /*out*/;
resourceInputs["deployedModels"] = undefined /*out*/;
resourceInputs["effectiveLabels"] = undefined /*out*/;
resourceInputs["etag"] = undefined /*out*/;
resourceInputs["modelDeploymentMonitoringJob"] = undefined /*out*/;
resourceInputs["pulumiLabels"] = undefined /*out*/;
resourceInputs["updateTime"] = undefined /*out*/;
}
opts = pulumi.mergeOptions(utilities.resourceOptsDefaults(), opts);
const secretOpts = { additionalSecretOutputs: ["effectiveLabels", "pulumiLabels"] };
opts = pulumi.mergeOptions(opts, secretOpts);
super(AiEndpoint.__pulumiType, name, resourceInputs, opts);
}
}
exports.AiEndpoint = AiEndpoint;
/** @internal */
AiEndpoint.__pulumiType = 'gcp:vertex/aiEndpoint:AiEndpoint';
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