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Google Cloud v8.27.0 published on Thursday, Apr 17, 2025 by Pulumi
gcp.vertex.AiTensorboard
Explore with Pulumi AI
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:
- API documentation
- How-to Guides
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(GetProjectArgs.builder()
.build());
var cryptoKey = new CryptoKeyIAMMember("cryptoKey", CryptoKeyIAMMemberArgs.builder()
.cryptoKeyId("kms-name")
.role("roles/cloudkms.cryptoKeyEncrypterDecrypter")
.member(String.format("serviceAccount:service-%s@gcp-sa-aiplatform.iam.gserviceaccount.com", project.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:
- Display
Name string - User provided name of this Tensorboard.
- Description string
- Description of this Tensorboard.
- Encryption
Spec AiTensorboard Encryption Spec - 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_labelsfor 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 string - User provided name of this Tensorboard.
- Description string
- Description of this Tensorboard.
- Encryption
Spec AiTensorboard Encryption Spec Args - 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_labelsfor 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 String - User provided name of this Tensorboard.
- description String
- Description of this Tensorboard.
- encryption
Spec AiTensorboard Encryption Spec - 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_labelsfor 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 string - User provided name of this Tensorboard.
- description string
- Description of this Tensorboard.
- encryption
Spec AiTensorboard Encryption Spec - 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_labelsfor 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 AiTensorboard Encryption Spec Args - 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_labelsfor 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
- display
Name String - User provided name of this Tensorboard.
- description String
- Description of this Tensorboard.
- encryption
Spec 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_labelsfor 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:
- Blob
Storage stringPath Prefix - 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 string - The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Effective
Labels 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.
- Pulumi
Labels Dictionary<string, string> - The combination of labels configured directly on the resource and default labels configured on the provider.
- Run
Count string - The number of Runs stored in this Tensorboard.
- Update
Time 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 stringPath Prefix - 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 string - The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- Effective
Labels 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.
- Pulumi
Labels map[string]string - The combination of labels configured directly on the resource and default labels configured on the provider.
- Run
Count string - The number of Runs stored in this Tensorboard.
- Update
Time 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 StringPath Prefix - 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 String - The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective
Labels 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.
- pulumi
Labels Map<String,String> - The combination of labels configured directly on the resource and default labels configured on the provider.
- run
Count String - The number of Runs stored in this Tensorboard.
- update
Time 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 stringPath Prefix - 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 string - The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective
Labels {[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.
- pulumi
Labels {[key: string]: string} - The combination of labels configured directly on the resource and default labels configured on the provider.
- run
Count string - The number of Runs stored in this Tensorboard.
- update
Time 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_ strpath_ prefix - 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.
- blob
Storage StringPath Prefix - 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 String - The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
- effective
Labels 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.
- pulumi
Labels Map<String> - The combination of labels configured directly on the resource and default labels configured on the provider.
- run
Count String - The number of Runs stored in this Tensorboard.
- update
Time 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) -> AiTensorboardfunc 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)resources: _: type: gcp:vertex:AiTensorboard get: id: ${id}- 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.
- Blob
Storage stringPath Prefix - 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 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.
- Display
Name string - User provided name of this Tensorboard.
- Effective
Labels 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.
- Encryption
Spec AiTensorboard Encryption Spec - 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_labelsfor 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.
- Pulumi
Labels 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
- Run
Count string - The number of Runs stored in this Tensorboard.
- Update
Time 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 stringPath Prefix - 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 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.
- Display
Name string - User provided name of this Tensorboard.
- Effective
Labels 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.
- Encryption
Spec AiTensorboard Encryption Spec Args - 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_labelsfor 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.
- Pulumi
Labels 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
- Run
Count string - The number of Runs stored in this Tensorboard.
- Update
Time 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 StringPath Prefix - 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 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.
- display
Name String - User provided name of this Tensorboard.
- effective
Labels 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.
- encryption
Spec AiTensorboard Encryption Spec - 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_labelsfor 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.
- pulumi
Labels 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
- run
Count String - The number of Runs stored in this Tensorboard.
- update
Time 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 stringPath Prefix - 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 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.
- display
Name string - User provided name of this Tensorboard.
- effective
Labels {[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.
- encryption
Spec AiTensorboard Encryption Spec - 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_labelsfor 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.
- pulumi
Labels {[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
- run
Count string - The number of Runs stored in this Tensorboard.
- update
Time 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_ strpath_ prefix - 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 AiTensorboard Encryption Spec Args - 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_labelsfor 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.
- blob
Storage StringPath Prefix - 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 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.
- display
Name String - User provided name of this Tensorboard.
- effective
Labels Map<String> - All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
- encryption
Spec 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_labelsfor 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.
- pulumi
Labels 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
- run
Count String - The number of Runs stored in this Tensorboard.
- update
Time 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
- Kms
Key stringName - 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 stringName - 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 StringName - 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 stringName - 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_ strname - 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 StringName - 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-betaTerraform Provider.