google.cloud.gcp_vertexai_featurestore_info module – List VertexAI.Featurestore resources
Note
This module is part of the google.cloud collection (version 1.15.0).
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_featurestore_info.
Synopsis
A collection of DataItems and Annotations on them.
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:
|
|
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. |
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A list of filter expression strings used to filter the resources returned by the API. Each string is a filter expression (e.g. Multiple expressions are combined with a logical AND. Refer to the filter topic documentation https://cloud.google.com/sdk/gcloud/reference/topic/filters. Refer to the AIP-160 filter syntax documentation https://google.aip.dev/160. |
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The Google Cloud Platform project to use. |
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The region of the dataset. eg us-central1. |
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Array of scopes to be used. |
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The contents of a Service Account JSON file, either in a dictionary or as a JSON string that represents it. |
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An optional service account email address if machineaccount is selected and the user does not wish to use the default email. |
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The path of a Service Account JSON file if serviceaccount is selected as type. |
Notes
Note
API Reference: https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featurestores
Official Documentation Guide: https://cloud.google.com/vertex-ai/docs
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: List all gcp_vertexai_featurestore_info resources
google.cloud.gcp_vertexai_featurestore_info:
project: "{{ gcp_project }}"
auth_kind: "{{ gcp_cred_kind }}"
service_account_file: "{{ gcp_cred_file }}"
register: result
- name: List gcp_vertexai_featurestore_info resources matching given filters
google.cloud.gcp_vertexai_featurestore_info:
filters:
- display_name = "my-resource"
project: "{{ gcp_project }}"
auth_kind: "{{ gcp_cred_kind }}"
service_account_file: "{{ gcp_cred_file }}"
register: result
Return Values
Common return values are documented here, the following are the fields unique to this module:
Key |
Description |
|---|---|
Whether any changes were made (always false for info modules). Returned: always |
|
List of VertexAI.Featurestore resources matching the supplied filters. May be empty, contain a single resource, or multiple resources. Returned: always |
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The timestamp of when the featurestore was created in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success |
|
If set, both of the online and offline data storage will be secured by this key. Returned: when set |
|
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 compute resource is created. Returned: always |
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A set of key/value label pairs to assign to this Featurestore. **Note**: This field is non-authoritative, and will only manage the labels present in your configuration. Returned: when set |
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Config for online serving resources. Returned: when set |
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The number of nodes for each cluster. The number of nodes will not scale automatically but can be scaled manually by providing different values when updating. Returned: when set |
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Online serving scaling configuration. Only one of fixedNodeCount and scaling can be set. Setting one will reset the other. Returned: when set |
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The maximum number of nodes to scale up to. Must be greater than minNodeCount, and less than or equal to 10 times of ‘minNodeCount’. Returned: always |
|
The minimum number of nodes to scale down to. Must be greater than or equal to 1. Returned: always |
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TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than onlineStorageTtlDays since the feature generation time. Note that onlineStorageTtlDays should be less than or equal to offlineStorageTtlDays for each EntityType under a featurestore. If not set, default to 4000 days. Returned: when set |
|
The timestamp of when the featurestore was last updated in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success |