gcloud ai tensorboards create

NAME: gcloud ai tensorboards create - create a new Vertex AI Tensorboard
SYNOPSIS: gcloud ai tensorboards create --display-name = DISPLAY_NAME [ --description = DESCRIPTION ] [ --labels =[ KEY = VALUE , …]] [ --region = REGION ] [ --kms-key = KMS_KEY : --kms-keyring = KMS_KEYRING --kms-location = KMS_LOCATION --kms-project = KMS_PROJECT ] [ GCLOUD_WIDE_FLAG … ]
DESCRIPTION: Create a new Vertex AI Tensorboard.
EXAMPLES: To create a Tensorboard with the display name my tensorboard :
gcloud ai tensorboards create --display-name = "my tensorboard"

You may also provide a description:

gcloud ai tensorboards create --description = "my description"

You may also provide labels:

gcloud ai tensorboards create --labels = "label1=value1" --labels = "label2=value2"
REQUIRED FLAGS: --display-name = DISPLAY_NAME

Display name of the tensorboard.
OPTIONAL FLAGS: --description = DESCRIPTION

Description of the tensorboard.

--labels =[ KEY = VALUE ,…]

List of label KEY=VALUE pairs to add.
Keys must start with a lowercase character and contain only hyphens ( - ), underscores ( _ ), lowercase characters, and numbers. Values must contain only hyphens ( - ), underscores ( _ ), lowercase characters, and numbers.

Region resource - Cloud region to create a Tensorboard. This represents a Cloud resource. (NOTE) Some attributes are not given arguments in this group but can be set in other ways.
To set the project attribute:

provide the argument --region on the command line with a fully specified name;

set the property ai/region with a fully specified name;

choose one from the prompted list of available regions with a fully specified name;

provide the argument --project on the command line;

set the property core/project .

--region = REGION

ID of the region or fully qualified identifier for the region.
To set the region attribute:

provide the argument --region on the command line;

set the property ai/region ;

choose one from the prompted list of available regions.

Key resource - The Cloud KMS (Key Management Service) cryptokey that will be used to protect the tensorboard. The 'Vertex AI Service Agent' service account must hold permission 'Cloud KMS CryptoKey Encrypter/Decrypter'. The arguments in this group can be used to specify the attributes of this resource.

--kms-key = KMS_KEY

ID of the key or fully qualified identifier for the key.
To set the kms-key attribute:

provide the argument --kms-key on the command line.

This flag argument must be specified if any of the other arguments in this group are specified.

--kms-keyring = KMS_KEYRING

The KMS keyring of the key.
To set the kms-keyring attribute:

provide the argument --kms-key on the command line with a fully specified name;

provide the argument --kms-keyring on the command line.

--kms-location = KMS_LOCATION

The Google Cloud location for the key.
To set the kms-location attribute:

provide the argument --kms-key on the command line with a fully specified name;

provide the argument --kms-location on the command line.

--kms-project = KMS_PROJECT

The Google Cloud project for the key.
To set the kms-project attribute:

provide the argument --kms-key on the command line with a fully specified name;

provide the argument --kms-project on the command line;

set the property core/project .
GCLOUD WIDE FLAGS: These flags are available to all commands: --access-token-file , --account , --billing-project , --configuration , --flags-file , --flatten , --format , --help , --impersonate-service-account , --log-http , --project , --quiet , --trace-token , --user-output-enabled , --verbosity .
Run $ gcloud help for details.
NOTES: These variants are also available:
gcloud alpha ai tensorboards create

gcloud beta ai tensorboards create

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gcloud ai tensorboards create