google_vertex_ai_feature_online_store

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.

To get more information about FeatureOnlineStore, see:

Open in Cloud Shell

Example Usage - Vertex Ai Feature Online Store

resource "google_vertex_ai_feature_online_store" "feature_online_store" {
  name = "example_feature_online_store"
  labels = {
    foo = "bar"
  }
  region = "us-central1"
  bigtable {
    auto_scaling {
      min_node_count         = 1
      max_node_count         = 3
      cpu_utilization_target = 50
    }
  }
}
Open in Cloud Shell

Example Usage - Vertex Ai Featureonlinestore With Beta Fields Optimized

resource "google_vertex_ai_feature_online_store" "featureonlinestore" {
  provider = google-beta
  name     = "example_feature_online_store_optimized"
  labels = {
    foo = "bar"
  }
  region = "us-central1"
  optimized {}
  dedicated_serving_endpoint {
    private_service_connect_config {
      enable_private_service_connect = true
      project_allowlist              = [data.google_project.project.number]
    }
  }
}

data "google_project" "project" {
  provider = google-beta
}
Open in Cloud Shell

Example Usage - Vertex Ai Featureonlinestore With Beta Fields Bigtable

resource "google_vertex_ai_feature_online_store" "featureonlinestore" {
  provider = google-beta
  name     = "example_feature_online_store_beta_bigtable"
  labels = {
    foo = "bar"
  }
  region = "us-central1"
  bigtable {
    auto_scaling {
      min_node_count         = 1
      max_node_count         = 2
      cpu_utilization_target = 80
    }
  }
  embedding_management {
    enabled = true
  }
  force_destroy = true
}

data "google_project" "project" {
  provider = google-beta
}

Argument Reference

The following arguments are supported:


The bigtable block supports:

The auto_scaling block supports:

The dedicated_serving_endpoint block supports:

The private_service_connect_config block supports:

The embedding_management block supports:

Attributes Reference

In addition to the arguments listed above, the following computed attributes are exported:

Timeouts

This resource provides the following Timeouts configuration options:

Import

FeatureOnlineStore can be imported using any of these accepted formats:

In Terraform v1.5.0 and later, use an import block to import FeatureOnlineStore using one of the formats above. For example:

import {
  id = "projects/{{project}}/locations/{{region}}/featureOnlineStores/{{name}}"
  to = google_vertex_ai_feature_online_store.default
}

When using the terraform import command, FeatureOnlineStore can be imported using one of the formats above. For example:

$ terraform import google_vertex_ai_feature_online_store.default projects/{{project}}/locations/{{region}}/featureOnlineStores/{{name}}
$ terraform import google_vertex_ai_feature_online_store.default {{project}}/{{region}}/{{name}}
$ terraform import google_vertex_ai_feature_online_store.default {{region}}/{{name}}
$ terraform import google_vertex_ai_feature_online_store.default {{name}}

User Project Overrides

This resource supports User Project Overrides.