google.cloud.gcp_vertexai_featurestore module – Creates a GCP VertexAI.Featurestore 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_featurestore.

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

access_token

string

The access token used to authenticate.

auth_kind

string / required

The type of credential used.

Choices:

  • "accesstoken"

  • "application"

  • "machineaccount"

  • "serviceaccount"

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 EntityTypes and Features for this Featurestore will also be deleted.

Choices:

  • false ← (default)

  • true

labels

dictionary

A set of key/value label pairs to assign to this Featurestore.

name

string / required

The name of the Featurestore.

This value may be up to 60 characters, and valid characters are [a-z0-9_].

The first character cannot be a number.

online_serving_config

dictionary

Config for online serving resources.

fixed_node_count

integer

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.

scaling

dictionary

Online serving scaling configuration.

Only one of fixedNodeCount and scaling can be set.

Setting one will reset the other.

max_node_count

integer / required

The maximum number of nodes to scale up to.

Must be greater than 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.

online_storage_ttl_days

integer

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.

Default: 4000

project

string

The Google Cloud Platform project to use.

region

string

The region of the dataset.

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

Examples

- name: Create Featurestore
  google.cloud.gcp_vertexai_featurestore:
    state: present
    name: "{{ resource_name }}"
    region: us-central1
    online_serving_config:
      fixed_node_count: 2
    project: "{{ gcp_project }}"
    auth_kind: "{{ gcp_cred_kind }}"
    service_account_file: "{{ gcp_cred_file }}"
  register: _myfs

- name: Delete Featurestore
  google.cloud.gcp_vertexai_featurestore:
    state: absent
    name: "{{ _myfs.name }}"
    region: us-central1
    project: "{{ gcp_project }}"
    auth_kind: "{{ gcp_cred_kind }}"
    service_account_file: "{{ gcp_cred_file }}"

################################################################################

- name: Create Featurestore with scaling configuration
  google.cloud.gcp_vertexai_featurestore:
    state: present
    name: "{{ resource_name }}"
    region: us-central1
    online_serving_config:
      scaling:
        min_node_count: 1
        max_node_count: 10
    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 featurestore 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 current state of the resource.

Returned: always

updateTime

string

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

Authors

  • Google Inc. (@googlecloudplatform)