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Google Cloud Classic v8.9.3 published on Monday, Nov 18, 2024 by Pulumi
pulumi/pulumi-gcp

gcp.vertex.AiTensorboard

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Google Cloud Classic v8.9.3 published on Monday, Nov 18, 2024 by Pulumi
pulumi/pulumi-gcp

    Tensorboard is a physical database that stores users’ training metrics. A default Tensorboard is provided in each region of a GCP project. If needed users can also create extra Tensorboards in their projects.

    To get more information about Tensorboard, see:

    Example Usage

    Vertex Ai Tensorboard

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const tensorboard = new gcp.vertex.AiTensorboard("tensorboard", {
    displayName: "terraform",
    description: "sample description",
    labels: {
        key1: "value1",
        key2: "value2",
    },
    region: "us-central1",
});

    import pulumi
import pulumi_gcp as gcp

tensorboard = gcp.vertex.AiTensorboard("tensorboard",
    display_name="terraform",
    description="sample description",
    labels={
        "key1": "value1",
        "key2": "value2",
    },
    region="us-central1")

    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.NewAiTensorboard(ctx, "tensorboard", &vertex.AiTensorboardArgs{
			DisplayName: pulumi.String("terraform"),
			Description: pulumi.String("sample description"),
			Labels: pulumi.StringMap{
				"key1": pulumi.String("value1"),
				"key2": pulumi.String("value2"),
			},
			Region: pulumi.String("us-central1"),
		})
		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 tensorboard = new Gcp.Vertex.AiTensorboard("tensorboard", new()
    {
        DisplayName = "terraform",
        Description = "sample description",
        Labels = 
        {
            { "key1", "value1" },
            { "key2", "value2" },
        },
        Region = "us-central1",
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiTensorboard;
import com.pulumi.gcp.vertex.AiTensorboardArgs;
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 tensorboard = new AiTensorboard("tensorboard", AiTensorboardArgs.builder()
            .displayName("terraform")
            .description("sample description")
            .labels(Map.ofEntries(
                Map.entry("key1", "value1"),
                Map.entry("key2", "value2")
            ))
            .region("us-central1")
            .build());

    }
}

    resources:
  tensorboard:
    type: gcp:vertex:AiTensorboard
    properties:
      displayName: terraform
      description: sample description
      labels:
        key1: value1
        key2: value2
      region: us-central1

    Vertex Ai Tensorboard Full

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const project = gcp.organizations.getProject({});
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`),
});
const tensorboard = new gcp.vertex.AiTensorboard("tensorboard", {
    displayName: "terraform",
    description: "sample description",
    labels: {
        key1: "value1",
        key2: "value2",
    },
    region: "us-central1",
    encryptionSpec: {
        kmsKeyName: "kms-name",
    },
}, {
    dependsOn: [cryptoKey],
});

    import pulumi
import pulumi_gcp as gcp

project = gcp.organizations.get_project()
crypto_key = gcp.kms.CryptoKeyIAMMember("crypto_key",
    crypto_key_id="kms-name",
    role="roles/cloudkms.cryptoKeyEncrypterDecrypter",
    member=f"serviceAccount:service-{project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com")
tensorboard = gcp.vertex.AiTensorboard("tensorboard",
    display_name="terraform",
    description="sample description",
    labels={
        "key1": "value1",
        "key2": "value2",
    },
    region="us-central1",
    encryption_spec={
        "kms_key_name": "kms-name",
    },
    opts = pulumi.ResourceOptions(depends_on=[crypto_key]))

    package main

import (
	"fmt"

	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/kms"
	"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
		}
		cryptoKey, err := kms.NewCryptoKeyIAMMember(ctx, "crypto_key", &kms.CryptoKeyIAMMemberArgs{
			CryptoKeyId: pulumi.String("kms-name"),
			Role:        pulumi.String("roles/cloudkms.cryptoKeyEncrypterDecrypter"),
			Member:      pulumi.Sprintf("serviceAccount:service-%v@gcp-sa-aiplatform.iam.gserviceaccount.com", project.Number),
		})
		if err != nil {
			return err
		}
		_, err = vertex.NewAiTensorboard(ctx, "tensorboard", &vertex.AiTensorboardArgs{
			DisplayName: pulumi.String("terraform"),
			Description: pulumi.String("sample description"),
			Labels: pulumi.StringMap{
				"key1": pulumi.String("value1"),
				"key2": pulumi.String("value2"),
			},
			Region: pulumi.String("us-central1"),
			EncryptionSpec: &vertex.AiTensorboardEncryptionSpecArgs{
				KmsKeyName: pulumi.String("kms-name"),
			},
		}, pulumi.DependsOn([]pulumi.Resource{
			cryptoKey,
		}))
		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 cryptoKey = new Gcp.Kms.CryptoKeyIAMMember("crypto_key", new()
    {
        CryptoKeyId = "kms-name",
        Role = "roles/cloudkms.cryptoKeyEncrypterDecrypter",
        Member = $"serviceAccount:service-{project.Apply(getProjectResult => getProjectResult.Number)}@gcp-sa-aiplatform.iam.gserviceaccount.com",
    });

    var tensorboard = new Gcp.Vertex.AiTensorboard("tensorboard", new()
    {
        DisplayName = "terraform",
        Description = "sample description",
        Labels = 
        {
            { "key1", "value1" },
            { "key2", "value2" },
        },
        Region = "us-central1",
        EncryptionSpec = new Gcp.Vertex.Inputs.AiTensorboardEncryptionSpecArgs
        {
            KmsKeyName = "kms-name",
        },
    }, new CustomResourceOptions
    {
        DependsOn =
        {
            cryptoKey,
        },
    });

});

    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.kms.CryptoKeyIAMMember;
import com.pulumi.gcp.kms.CryptoKeyIAMMemberArgs;
import com.pulumi.gcp.vertex.AiTensorboard;
import com.pulumi.gcp.vertex.AiTensorboardArgs;
import com.pulumi.gcp.vertex.inputs.AiTensorboardEncryptionSpecArgs;
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 project = OrganizationsFunctions.getProject();

        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());

        var tensorboard = new AiTensorboard("tensorboard", AiTensorboardArgs.builder()
            .displayName("terraform")
            .description("sample description")
            .labels(Map.ofEntries(
                Map.entry("key1", "value1"),
                Map.entry("key2", "value2")
            ))
            .region("us-central1")
            .encryptionSpec(AiTensorboardEncryptionSpecArgs.builder()
                .kmsKeyName("kms-name")
                .build())
            .build(), CustomResourceOptions.builder()
                .dependsOn(cryptoKey)
                .build());

    }
}

    resources:
  tensorboard:
    type: gcp:vertex:AiTensorboard
    properties:
      displayName: terraform
      description: sample description
      labels:
        key1: value1
        key2: value2
      region: us-central1
      encryptionSpec:
        kmsKeyName: kms-name
    options:
      dependson:
        - ${cryptoKey}
  cryptoKey:
    type: gcp:kms:CryptoKeyIAMMember
    name: crypto_key
    properties:
      cryptoKeyId: kms-name
      role: roles/cloudkms.cryptoKeyEncrypterDecrypter
      member: serviceAccount:service-${project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com
variables:
  project:
    fn::invoke:
      Function: gcp:organizations:getProject
      Arguments: {}

    Create AiTensorboard Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new AiTensorboard(name: string, args: AiTensorboardArgs, opts?: CustomResourceOptions);
    @overload
def AiTensorboard(resource_name: str,
                  args: AiTensorboardArgs,
                  opts: Optional[ResourceOptions] = None)

@overload
def AiTensorboard(resource_name: str,
                  opts: Optional[ResourceOptions] = None,
                  display_name: Optional[str] = None,
                  description: Optional[str] = None,
                  encryption_spec: Optional[AiTensorboardEncryptionSpecArgs] = None,
                  labels: Optional[Mapping[str, str]] = None,
                  project: Optional[str] = None,
                  region: Optional[str] = None)
    func NewAiTensorboard(ctx *Context, name string, args AiTensorboardArgs, opts ...ResourceOption) (*AiTensorboard, error)
    public AiTensorboard(string name, AiTensorboardArgs args, CustomResourceOptions? opts = null)
    public AiTensorboard(String name, AiTensorboardArgs args)
public AiTensorboard(String name, AiTensorboardArgs args, CustomResourceOptions options)

    type: gcp:vertex:AiTensorboard
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 AiTensorboardArgs
    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 AiTensorboardArgs
    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 AiTensorboardArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args AiTensorboardArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args AiTensorboardArgs
    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 aiTensorboardResource = new Gcp.Vertex.AiTensorboard("aiTensorboardResource", new()
{
    DisplayName = "string",
    Description = "string",
    EncryptionSpec = new Gcp.Vertex.Inputs.AiTensorboardEncryptionSpecArgs
    {
        KmsKeyName = "string",
    },
    Labels = 
    {
        { "string", "string" },
    },
    Project = "string",
    Region = "string",
});

    example, err := vertex.NewAiTensorboard(ctx, "aiTensorboardResource", &vertex.AiTensorboardArgs{
	DisplayName: pulumi.String("string"),
	Description: pulumi.String("string"),
	EncryptionSpec: &vertex.AiTensorboardEncryptionSpecArgs{
		KmsKeyName: pulumi.String("string"),
	},
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Project: pulumi.String("string"),
	Region:  pulumi.String("string"),
})

    var aiTensorboardResource = new AiTensorboard("aiTensorboardResource", AiTensorboardArgs.builder()
    .displayName("string")
    .description("string")
    .encryptionSpec(AiTensorboardEncryptionSpecArgs.builder()
        .kmsKeyName("string")
        .build())
    .labels(Map.of("string", "string"))
    .project("string")
    .region("string")
    .build());

    ai_tensorboard_resource = gcp.vertex.AiTensorboard("aiTensorboardResource",
    display_name="string",
    description="string",
    encryption_spec={
        "kms_key_name": "string",
    },
    labels={
        "string": "string",
    },
    project="string",
    region="string")

    const aiTensorboardResource = new gcp.vertex.AiTensorboard("aiTensorboardResource", {
    displayName: "string",
    description: "string",
    encryptionSpec: {
        kmsKeyName: "string",
    },
    labels: {
        string: "string",
    },
    project: "string",
    region: "string",
});

    type: gcp:vertex:AiTensorboard
properties:
    description: string
    displayName: string
    encryptionSpec:
        kmsKeyName: string
    labels:
        string: string
    project: string
    region: string

    AiTensorboard 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 AiTensorboard resource accepts the following input properties:

    DisplayName string
    User provided name of this Tensorboard.

    Description string
    Description of this Tensorboard.
    EncryptionSpec AiTensorboardEncryptionSpec
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    Labels Dictionary<string, string>

    The labels with user-defined metadata to organize your Tensorboards.

    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.

    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 tensorboard. eg us-central1
    DisplayName string
    User provided name of this Tensorboard.

    Description string
    Description of this Tensorboard.
    EncryptionSpec AiTensorboardEncryptionSpecArgs
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    Labels map[string]string

    The labels with user-defined metadata to organize your Tensorboards.

    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.

    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 tensorboard. eg us-central1
    displayName String
    User provided name of this Tensorboard.

    description String
    Description of this Tensorboard.
    encryptionSpec AiTensorboardEncryptionSpec
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels Map<String,String>

    The labels with user-defined metadata to organize your Tensorboards.

    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.

    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 tensorboard. eg us-central1
    displayName string
    User provided name of this Tensorboard.

    description string
    Description of this Tensorboard.
    encryptionSpec AiTensorboardEncryptionSpec
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels {[key: string]: string}

    The labels with user-defined metadata to organize your Tensorboards.

    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.

    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 tensorboard. eg us-central1
    display_name str
    User provided name of this Tensorboard.

    description str
    Description of this Tensorboard.
    encryption_spec AiTensorboardEncryptionSpecArgs
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels Mapping[str, str]

    The labels with user-defined metadata to organize your Tensorboards.

    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.

    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 tensorboard. eg us-central1
    displayName String
    User provided name of this Tensorboard.

    description String
    Description of this Tensorboard.
    encryptionSpec Property Map
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels Map<String>

    The labels with user-defined metadata to organize your Tensorboards.

    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.

    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 tensorboard. eg us-central1

    Outputs

    All input properties are implicitly available as output properties. Additionally, the AiTensorboard resource produces the following output properties:

    BlobStoragePathPrefix string
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    CreateTime string
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    EffectiveLabels 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.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    Name of the Tensorboard.
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    RunCount string
    The number of Runs stored in this Tensorboard.
    UpdateTime string
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    BlobStoragePathPrefix string
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    CreateTime string
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    EffectiveLabels 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.
    Id string
    The provider-assigned unique ID for this managed resource.
    Name string
    Name of the Tensorboard.
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    RunCount string
    The number of Runs stored in this Tensorboard.
    UpdateTime string
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blobStoragePathPrefix String
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    createTime String
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    effectiveLabels 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.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    Name of the Tensorboard.
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    runCount String
    The number of Runs stored in this Tensorboard.
    updateTime String
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blobStoragePathPrefix string
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    createTime string
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    effectiveLabels {[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.
    id string
    The provider-assigned unique ID for this managed resource.
    name string
    Name of the Tensorboard.
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    runCount string
    The number of Runs stored in this Tensorboard.
    updateTime string
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blob_storage_path_prefix str
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    create_time str
    The timestamp of when the Tensorboard 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.
    id str
    The provider-assigned unique ID for this managed resource.
    name str
    Name of the Tensorboard.
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    run_count str
    The number of Runs stored in this Tensorboard.
    update_time str
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blobStoragePathPrefix String
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    createTime String
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    effectiveLabels Map<String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id String
    The provider-assigned unique ID for this managed resource.
    name String
    Name of the Tensorboard.
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    runCount String
    The number of Runs stored in this Tensorboard.
    updateTime String
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    Look up Existing AiTensorboard Resource

    Get an existing AiTensorboard 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?: AiTensorboardState, opts?: CustomResourceOptions): AiTensorboard
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        blob_storage_path_prefix: Optional[str] = None,
        create_time: Optional[str] = None,
        description: Optional[str] = None,
        display_name: Optional[str] = None,
        effective_labels: Optional[Mapping[str, str]] = None,
        encryption_spec: Optional[AiTensorboardEncryptionSpecArgs] = None,
        labels: Optional[Mapping[str, str]] = None,
        name: Optional[str] = None,
        project: Optional[str] = None,
        pulumi_labels: Optional[Mapping[str, str]] = None,
        region: Optional[str] = None,
        run_count: Optional[str] = None,
        update_time: Optional[str] = None) -> AiTensorboard
    func GetAiTensorboard(ctx *Context, name string, id IDInput, state *AiTensorboardState, opts ...ResourceOption) (*AiTensorboard, error)
    public static AiTensorboard Get(string name, Input<string> id, AiTensorboardState? state, CustomResourceOptions? opts = null)
    public static AiTensorboard get(String name, Output<String> id, AiTensorboardState 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.
    The following state arguments are supported:
    BlobStoragePathPrefix string
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    CreateTime string
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    Description string
    Description of this Tensorboard.
    DisplayName string
    User provided name of this Tensorboard.

    EffectiveLabels 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.
    EncryptionSpec AiTensorboardEncryptionSpec
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    Labels Dictionary<string, string>

    The labels with user-defined metadata to organize your Tensorboards.

    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
    Name of the Tensorboard.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    PulumiLabels 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 tensorboard. eg us-central1
    RunCount string
    The number of Runs stored in this Tensorboard.
    UpdateTime string
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    BlobStoragePathPrefix string
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    CreateTime string
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    Description string
    Description of this Tensorboard.
    DisplayName string
    User provided name of this Tensorboard.

    EffectiveLabels 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.
    EncryptionSpec AiTensorboardEncryptionSpecArgs
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    Labels map[string]string

    The labels with user-defined metadata to organize your Tensorboards.

    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
    Name of the Tensorboard.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    PulumiLabels 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 tensorboard. eg us-central1
    RunCount string
    The number of Runs stored in this Tensorboard.
    UpdateTime string
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blobStoragePathPrefix String
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    createTime String
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    description String
    Description of this Tensorboard.
    displayName String
    User provided name of this Tensorboard.

    effectiveLabels 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.
    encryptionSpec AiTensorboardEncryptionSpec
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels Map<String,String>

    The labels with user-defined metadata to organize your Tensorboards.

    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
    Name of the Tensorboard.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels 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 tensorboard. eg us-central1
    runCount String
    The number of Runs stored in this Tensorboard.
    updateTime String
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blobStoragePathPrefix string
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    createTime string
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    description string
    Description of this Tensorboard.
    displayName string
    User provided name of this Tensorboard.

    effectiveLabels {[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.
    encryptionSpec AiTensorboardEncryptionSpec
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels {[key: string]: string}

    The labels with user-defined metadata to organize your Tensorboards.

    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
    Name of the Tensorboard.
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels {[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 tensorboard. eg us-central1
    runCount string
    The number of Runs stored in this Tensorboard.
    updateTime string
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blob_storage_path_prefix str
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    create_time str
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    description str
    Description of this Tensorboard.
    display_name str
    User provided name of this Tensorboard.

    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 AiTensorboardEncryptionSpecArgs
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels Mapping[str, str]

    The labels with user-defined metadata to organize your Tensorboards.

    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
    Name of the Tensorboard.
    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 tensorboard. eg us-central1
    run_count str
    The number of Runs stored in this Tensorboard.
    update_time str
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    blobStoragePathPrefix String
    Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'.
    createTime String
    The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
    description String
    Description of this Tensorboard.
    displayName String
    User provided name of this Tensorboard.

    effectiveLabels Map<String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    encryptionSpec Property Map
    Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. Structure is documented below.
    labels Map<String>

    The labels with user-defined metadata to organize your Tensorboards.

    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
    Name of the Tensorboard.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    region String
    The region of the tensorboard. eg us-central1
    runCount String
    The number of Runs stored in this Tensorboard.
    updateTime String
    The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.

    Supporting Types

    AiTensorboardEncryptionSpec, AiTensorboardEncryptionSpecArgs

    KmsKeyName string
    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 resource is created.
    KmsKeyName string
    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 resource is created.
    kmsKeyName String
    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 resource is created.
    kmsKeyName string
    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 resource is created.
    kms_key_name str
    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 resource is created.
    kmsKeyName String
    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 resource is created.

    Import

    Tensorboard can be imported using any of these accepted formats:

    • projects/{{project}}/locations/{{region}}/tensorboards/{{name}}

    • {{project}}/{{region}}/{{name}}

    • {{region}}/{{name}}

    • {{name}}

    When using the pulumi import command, Tensorboard can be imported using one of the formats above. For example:

    $ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default projects/{{project}}/locations/{{region}}/tensorboards/{{name}}

    $ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default {{project}}/{{region}}/{{name}}

    $ pulumi import gcp:vertex/aiTensorboard:AiTensorboard default {{region}}/{{name}}

    $ pulumi import gcp:vertex/aiTensorboard:AiTensorboard 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.
    gcp logo
    Google Cloud Classic v8.9.3 published on Monday, Nov 18, 2024 by Pulumi
    pulumi/pulumi-gcp