google.cloud.gcp_vertexai_tensorboard module – Creates a GCP VertexAI.Tensorboard resource

Note

This module is part of the google.cloud collection (version 1.13.0).

You might already have this collection installed if you are using the ansible package. It is not included in ansible-core. To check whether it is installed, run ansible-galaxy collection list.

To install it, use: ansible-galaxy collection install google.cloud. You need further requirements to be able to use this module, see Requirements for details.

To use it in a playbook, specify: google.cloud.gcp_vertexai_tensorboard.

Synopsis
Requirements
Parameters
Notes
Examples
Return Values

Synopsis

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.

Requirements

The below requirements are needed on the host that executes this module.

python >= 3.8
requests >= 2.18.4
google-auth >= 2.25.1

Parameters

Parameter	Comments
access_token string	The access token used to authenticate.
auth_kind string / required	The type of credential used. Choices: `"accesstoken"` `"application"` `"machineaccount"` `"serviceaccount"`
description string	Description of this Tensorboard.
display_name string / required	User provided name of this Tensorboard.
encryption_spec dictionary	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.
kms_key_name string / 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.
env_type string	Specifies which Ansible environment you’re running this module within. This should not be set unless you know what you’re doing. This only alters the User Agent string for any API requests.
labels dictionary	The labels with user-defined metadata to organize your Tensorboards.
project string	The Google Cloud Platform project to use.
region string	The region of the tensorboard. eg us-central1.
scopes list / elements=string	Array of scopes to be used.
service_account_contents jsonarg	The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it.
service_account_email string	An optional service account email address if machineaccount is selected and the user does not wish to use the default email.
service_account_file path	The path of a Service Account JSON file if serviceaccount is selected as type.
state string	Whether the resource should exist in GCP. Choices: `"present"` ← (default) `"absent"`

Notes

Note

API Reference: https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.tensorboards
Official Documentation Guide: https://cloud.google.com/vertex-ai/docs
For authentication, you can set auth_kind using the GCP_AUTH_KIND env variable.
For authentication, you can set service_account_file using the GCP_SERVICE_ACCOUNT_FILE env variable.
For authentication, you can set service_account_contents using the GCP_SERVICE_ACCOUNT_CONTENTS env variable.
For authentication, you can set service_account_email using the GCP_SERVICE_ACCOUNT_EMAIL env variable.
For authentication, you can set access_token using the GCP_ACCESS_TOKEN env variable.
For authentication, you can set scopes using the GCP_SCOPES env variable.
Environment variables values will only be used if the playbook values are not set.
The service_account_email, service_account_file, service_account_file and access_token options are mutually exclusive.

Examples

- name: Create Tensorboard
  google.cloud.gcp_vertexai_tensorboard:
    state: present
    display_name: my-tensorboard
    description: sample description
    labels:
      key1: value1
      key2: value2
    region: us-central1
    project: "{{ gcp_project }}"
    auth_kind: "{{ gcp_cred_kind }}"
    service_account_file: "{{ gcp_cred_file }}"

Return Values

Common return values are documented here, the following are the fields unique to this module:

Key	Description
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 ‘/’. Returned: success
changed boolean	Whether the resource was changed. Returned: always
createTime string	The timestamp of when the Tensorboard was created in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success
name string	Name of the Tensorboard. Returned: success
runCount string	The number of Runs stored in this Tensorboard. Returned: success
state string	The current state of the resource. Returned: always
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. Returned: success

Authors

Google Inc. (@googlecloudplatform)

Collection links

© 2012–2018 Michael DeHaan
© 2018–2025 Red Hat, Inc.
Licensed under the GNU General Public License version 3.
https://docs.ansible.com/projects/ansible/latest/collections/google/cloud/gcp_vertexai_tensorboard_module.html