google.cloud.gcp_vertexai_feature_group_feature module – Creates a GCP VertexAI.FeatureGroupFeature resource
Note
This module is part of the google.cloud collection (version 1.12.0).
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_feature_group_feature.
Synopsis
Vertex AI Feature Group Feature is feature metadata information.
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 |
|---|---|
The access token used to authenticate. |
|
The type of credential used. Choices:
|
|
The description of the FeatureGroup. |
|
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. |
|
The name of the Feature Group. |
|
The labels with user-defined metadata to organize your FeatureGroup. |
|
The resource name of the Feature Group Feature. |
|
The Google Cloud Platform project to use. |
|
The region for the resource. It should be the same as the feature group’s region. |
|
Array of scopes to be used. |
|
The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it. |
|
An optional service account email address if machineaccount is selected and the user does not wish to use the default email. |
|
The path of a Service Account JSON file if serviceaccount is selected as type. |
|
Whether the resource should exist in GCP. Choices:
|
|
The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use featureId. |
Notes
Note
API Reference: https://cloud.google.com/vertex-ai/docs/reference/rest/v1beta1/projects.locations.featureGroups.features
Creating a Feature Guide: https://cloud.google.com/vertex-ai/docs/featurestore/latest/create-feature
For authentication, you can set auth_kind using the
GCP_AUTH_KINDenv variable.For authentication, you can set service_account_file using the
GCP_SERVICE_ACCOUNT_FILEenv variable.For authentication, you can set service_account_contents using the
GCP_SERVICE_ACCOUNT_CONTENTSenv variable.For authentication, you can set service_account_email using the
GCP_SERVICE_ACCOUNT_EMAILenv variable.For authentication, you can set access_token using the
GCP_ACCESS_TOKENenv variable.For authentication, you can set scopes using the
GCP_SCOPESenv variable.Environment variables values will only be used if the playbook values are not set.
The
service_account_email,service_account_file,service_account_fileandaccess_tokenoptions are mutually exclusive.
Examples
- name: Create feature group feature
google.cloud.gcp_vertexai_feature_group_feature:
state: present
name: my_feature
feature_group: my_feature_group
description: "A simple feature group feature"
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 |
|---|---|
Whether the resource was changed. Returned: always |
|
The timestamp of when the FeatureGroup was created in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success |
|
The current state of the resource. Returned: always |
|
The timestamp of when the FeatureGroup was last updated in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success |