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:
resource "google_vertex_ai_tensorboard" "tensorboard" {
display_name = "terraform"
description = "sample description"
labels = {
"key1" : "value1",
"key2" : "value2"
}
region = "us-central1"
}
resource "google_vertex_ai_tensorboard" "tensorboard" {
display_name = "terraform"
description = "sample description"
labels = {
"key1" : "value1",
"key2" : "value2"
}
region = "us-central1"
encryption_spec {
kms_key_name = "kms-name"
}
depends_on = [google_kms_crypto_key_iam_member.crypto_key]
}
resource "google_kms_crypto_key_iam_member" "crypto_key" {
crypto_key_id = "kms-name"
role = "roles/cloudkms.cryptoKeyEncrypterDecrypter"
member = "serviceAccount:service-${data.google_project.project.number}@gcp-sa-aiplatform.iam.gserviceaccount.com"
}
data "google_project" "project" {}
The following arguments are supported:
display_name
-
(Required)
User provided name of this Tensorboard.description
-
(Optional)
Description of this Tensorboard.
encryption_spec
-
(Optional)
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
-
(Optional)
The labels with user-defined metadata to organize your Tensorboards.
Note: This field is non-authoritative, and will only manage the labels present in your configuration.
Please refer to the field effective_labels
for all of the labels present on the resource.
region
-
(Optional)
The region of the tensorboard. eg us-central1
project
- (Optional) The ID of the project in which the resource belongs.
If it is not provided, the provider project is used.
The encryption_spec
block supports:
kms_key_name
-
(Required)
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.In addition to the arguments listed above, the following computed attributes are exported:
id
- an identifier for the resource with format {{name}}
name
-
Name of the Tensorboard.
blob_storage_path_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 '/'.
run_count
-
The number of Runs stored in this Tensorboard.
create_time
-
The timestamp of when the Tensorboard was created in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
update_time
-
The timestamp of when the Tensorboard was last updated in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits.
terraform_labels
-
The combination of labels configured directly on the resource
and default labels configured on the provider.
effective_labels
-
All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Terraform, other clients and services.
This resource provides the following Timeouts configuration options:
create
- Default is 20 minutes.update
- Default is 20 minutes.delete
- Default is 20 minutes.Tensorboard can be imported using any of these accepted formats:
projects/{{project}}/locations/{{region}}/tensorboards/{{name}}
{{project}}/{{region}}/{{name}}
{{region}}/{{name}}
{{name}}
In Terraform v1.5.0 and later, use an import
block to import Tensorboard using one of the formats above. For example:
import {
id = "projects/{{project}}/locations/{{region}}/tensorboards/{{name}}"
to = google_vertex_ai_tensorboard.default
}
When using the terraform import
command, Tensorboard can be imported using one of the formats above. For example:
$ terraform import google_vertex_ai_tensorboard.default projects/{{project}}/locations/{{region}}/tensorboards/{{name}}
$ terraform import google_vertex_ai_tensorboard.default {{project}}/{{region}}/{{name}}
$ terraform import google_vertex_ai_tensorboard.default {{region}}/{{name}}
$ terraform import google_vertex_ai_tensorboard.default {{name}}
This resource supports User Project Overrides.