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Google Cloud Classic v6.48.0, Jan 24 23

gcp.vertex.AiTensorboard

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

using System.Collections.Generic;
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 main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v6/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
	})
}
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());

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

Vertex Ai Tensorboard Full

using System.Collections.Generic;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var project = Gcp.Organizations.GetProject.Invoke();

    var cryptoKey = new Gcp.Kms.CryptoKeyIAMMember("cryptoKey", 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 = new[]
        {
            cryptoKey,
        },
    });

});
package main

import (
	"fmt"

	"github.com/pulumi/pulumi-gcp/sdk/v6/go/gcp/kms"
	"github.com/pulumi/pulumi-gcp/sdk/v6/go/gcp/organizations"
	"github.com/pulumi/pulumi-gcp/sdk/v6/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, nil, nil)
		if err != nil {
			return err
		}
		cryptoKey, err := kms.NewCryptoKeyIAMMember(ctx, "cryptoKey", &kms.CryptoKeyIAMMemberArgs{
			CryptoKeyId: pulumi.String("kms-name"),
			Role:        pulumi.String("roles/cloudkms.cryptoKeyEncrypterDecrypter"),
			Member:      pulumi.String(fmt.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
	})
}
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());

    }
}
import pulumi
import pulumi_gcp as gcp

project = gcp.organizations.get_project()
crypto_key = gcp.kms.CryptoKeyIAMMember("cryptoKey",
    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=gcp.vertex.AiTensorboardEncryptionSpecArgs(
        kms_key_name="kms-name",
    ),
    opts=pulumi.ResourceOptions(depends_on=[crypto_key]))
import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const project = gcp.organizations.getProject({});
const cryptoKey = new gcp.kms.CryptoKeyIAMMember("cryptoKey", {
    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],
});
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:
        - ${cryptoKey}
  cryptoKey:
    type: gcp:kms:CryptoKeyIAMMember
    properties:
      cryptoKeyId: kms-name
      role: roles/cloudkms.cryptoKeyEncrypterDecrypter
      member: serviceAccount:service-${project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com
variables:
  project:
    fn::invoke:
      Function: gcp:organizations:getProject
      Arguments: {}

Create AiTensorboard Resource

new AiTensorboard(name: string, args: AiTensorboardArgs, opts?: CustomResourceOptions);
@overload
def AiTensorboard(resource_name: str,
                  opts: Optional[ResourceOptions] = None,
                  description: Optional[str] = None,
                  display_name: Optional[str] = None,
                  encryption_spec: Optional[AiTensorboardEncryptionSpecArgs] = None,
                  labels: Optional[Mapping[str, str]] = None,
                  project: Optional[str] = None,
                  region: Optional[str] = None)
@overload
def AiTensorboard(resource_name: str,
                  args: AiTensorboardArgs,
                  opts: Optional[ResourceOptions] = 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.

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.

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

The AiTensorboard resource accepts the following input properties:

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 Dictionary<string, string>

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

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.

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.

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 {[key: string]: string}

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

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.

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.

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.

Id string

The provider-assigned unique ID for this managed resource.

Name string

Name of the Tensorboard.

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.

Id string

The provider-assigned unique ID for this managed resource.

Name string

Name of the Tensorboard.

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.

id String

The provider-assigned unique ID for this managed resource.

name String

Name of the Tensorboard.

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.

id string

The provider-assigned unique ID for this managed resource.

name string

Name of the Tensorboard.

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.

id str

The provider-assigned unique ID for this managed resource.

name str

Name of the Tensorboard.

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.

id String

The provider-assigned unique ID for this managed resource.

name String

Name of the Tensorboard.

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,
        encryption_spec: Optional[AiTensorboardEncryptionSpecArgs] = None,
        labels: Optional[Mapping[str, str]] = None,
        name: Optional[str] = None,
        project: Optional[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.

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 Dictionary<string, string>

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

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.

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.

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.

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.

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.

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.

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.

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.

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 {[key: string]: string}

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

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.

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.

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.

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.

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.

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.

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.

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

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

 $ 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}}

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.