google.cloud.gcp_vertexai_feature_online_store module – Creates a GCP VertexAI.FeatureOnlineStore 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_feature_online_store.

Synopsis
Requirements
Parameters
Notes
Examples
Return Values

Synopsis

Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container.

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"`
bigtable dictionary	Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
auto_scaling dictionary / required	Autoscaling config applied to Bigtable Instance.
cpu_utilization_target integer	A percentage of the cluster’s CPU capacity. Can be from 10% to 80%. When a cluster’s CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%.
max_node_count integer / required	The maximum number of nodes to scale up to. Must be greater than or equal to minNodeCount, and less than or equal to 10 times of ‘minNodeCount’.
min_node_count integer / required	The minimum number of nodes to scale down to. Must be greater than or equal to 1.
enable_direct_bigtable_access boolean	If true, enable direct access to the Bigtable instance. Choices: `false` `true`
zone string	The zone where the Bigtable instance will be created.
dedicated_serving_endpoint dictionary	The dedicated serving endpoint for this FeatureOnlineStore, which is different from common vertex service endpoint. Only need to be set when you choose Optimized storage type or enable EmbeddingManagement. Will use public endpoint by default.
private_service_connect_config dictionary	Private service connect config.
enable_private_service_connect boolean / required	If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint. Choices: `false` `true`
project_allowlist list / elements=string	A list of Projects from which the forwarding rule will target the service attachment.
public_endpoint_domain_name string	Domain name to use for this FeatureOnlineStore.
service_attachment string	Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created.
embedding_management dictionary	The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype.
enabled boolean	Enable embedding management. Choices: `false` `true`
encryption_spec dictionary	If set, both of the online and offline data storage 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 compute 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.
force_destroy boolean	If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted. Choices: `false` ← (default) `true`
labels dictionary	The labels with user-defined metadata to organize your feature online stores.
name string / required	The resource name of the Feature Online Store. This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.
optimized dictionary	Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore.
project string	The Google Cloud Platform project to use.
region string	The region of feature online store. 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.featureOnlineStores
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 Feature Online Store
  google.cloud.gcp_vertexai_feature_online_store:
    state: present
    name: my_feature_online_store
    bigtable:
      auto_scaling:
        min_node_count: 1
        max_node_count: 3
        cpu_utilization_target: 50
    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
changed boolean	Whether the resource was changed. Returned: always
createTime string	The timestamp of when the feature online store was created in RFC3339 UTC “Zulu” format, with nanosecond resolution and up to nine fractional digits. Returned: success
etag string	Used to perform consistent read-modify-write updates. Returned: success
state string	The state of the Feature Online Store. See the possible states in [this link](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.featureOnlineStores#state). Returned: success
updateTime string	The timestamp of when the feature online store 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_feature_online_store_module.html