google.cloud.gcp_vertexai_feature_online_store_info module – List VertexAI.FeatureOnlineStore 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_feature_online_store_info.
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 |
|---|---|
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. |
|
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 feature online store. 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.featureOnlineStores
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_feature_online_store_info resources
google.cloud.gcp_vertexai_feature_online_store_info:
project: "{{ gcp_project }}"
auth_kind: "{{ gcp_cred_kind }}"
service_account_file: "{{ gcp_cred_file }}"
register: result
- name: List gcp_vertexai_feature_online_store_info resources matching given filters
google.cloud.gcp_vertexai_feature_online_store_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.FeatureOnlineStore resources matching the supplied filters. May be empty, contain a single resource, or multiple resources. Returned: always |
|
Settings for Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Returned: when set |
|
Autoscaling config applied to Bigtable Instance. Returned: always |
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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%. Returned: when set |
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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’. Returned: always |
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The minimum number of nodes to scale down to. Must be greater than or equal to 1. Returned: always |
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If true, enable direct access to the Bigtable instance. Returned: when set |
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The zone where the Bigtable instance will be created. Returned: when set |
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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 |
|
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. Returned: when set |
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Private service connect config. Returned: when set |
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If set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint. Returned: always |
|
A list of Projects from which the forwarding rule will target the service attachment. Returned: when set |
|
Domain name to use for this FeatureOnlineStore. Returned: success |
|
Name of the service attachment resource. Applicable only if private service connect is enabled and after FeatureViewSync is created. Returned: success |
|
The settings for embedding management in FeatureOnlineStore. Embedding management can only be set for BigTable. It is enabled by default for optimized storagetype. Returned: when set |
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Enable embedding management. Returned: when set |
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If set, both of the online and offline data storage will be secured by this key. Returned: when set |
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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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The labels with user-defined metadata to organize your feature online stores. **Note**: This field is non-authoritative, and will only manage the labels present in your configuration. Returned: when set |
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Settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. Returned: when set |
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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 |
|
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 |