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Google Cloud Classic v6.58.0 published on Tuesday, Jun 6, 2023 by Pulumi

gcp.vertex.AiTensorboard

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Google Cloud Classic v6.58.0 published on Tuesday, Jun 6, 2023 by Pulumi

    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 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 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 System.Linq;
    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.

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    Google Cloud Classic v6.58.0 published on Tuesday, Jun 6, 2023 by Pulumi