IAM policy for Vertex AI FeaturestoreEntitytype

Three different resources help you manage your IAM policy for Vertex AI FeaturestoreEntitytype. Each of these resources serves a different use case:

A data source can be used to retrieve policy data in advent you do not need creation

google_vertex_ai_featurestore_entitytype_iam_policy

data "google_iam_policy" "admin" {
  binding {
    role = "roles/viewer"
    members = [
      "user:jane@example.com",
    ]
  }
}

resource "google_vertex_ai_featurestore_entitytype_iam_policy" "policy" {
  featurestore = google_vertex_ai_featurestore_entitytype.entity.featurestore
  entitytype = google_vertex_ai_featurestore_entitytype.entity.name
  policy_data = data.google_iam_policy.admin.policy_data
}

google_vertex_ai_featurestore_entitytype_iam_binding

resource "google_vertex_ai_featurestore_entitytype_iam_binding" "binding" {
  featurestore = google_vertex_ai_featurestore_entitytype.entity.featurestore
  entitytype = google_vertex_ai_featurestore_entitytype.entity.name
  role = "roles/viewer"
  members = [
    "user:jane@example.com",
  ]
}

google_vertex_ai_featurestore_entitytype_iam_member

resource "google_vertex_ai_featurestore_entitytype_iam_member" "member" {
  featurestore = google_vertex_ai_featurestore_entitytype.entity.featurestore
  entitytype = google_vertex_ai_featurestore_entitytype.entity.name
  role = "roles/viewer"
  member = "user:jane@example.com"
}

Argument Reference

The following arguments are supported:

Attributes Reference

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

Import

For all import syntaxes, the "resource in question" can take any of the following forms:

Any variables not passed in the import command will be taken from the provider configuration.

Vertex AI featurestoreentitytype IAM resources can be imported using the resource identifiers, role, and member.

IAM member imports use space-delimited identifiers: the resource in question, the role, and the member identity, e.g.

$ terraform import google_vertex_ai_featurestore_entitytype_iam_member.editor "{{featurestore}}/entityTypes/{{featurestore_entitytype}} roles/viewer user:jane@example.com"

IAM binding imports use space-delimited identifiers: the resource in question and the role, e.g.

$ terraform import google_vertex_ai_featurestore_entitytype_iam_binding.editor "{{featurestore}}/entityTypes/{{featurestore_entitytype}} roles/viewer"

IAM policy imports use the identifier of the resource in question, e.g.

$ terraform import google_vertex_ai_featurestore_entitytype_iam_policy.editor {{featurestore}}/entityTypes/{{featurestore_entitytype}}