Google BigQuery Table IAM
This page shows how to write Terraform for BigQuery Table IAM and write them securely.
The Table IAM in BigQuery can be configured in Terraform with the resource name
google_bigquery_table_iam. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
The following arguments are supported:
project- (Optional) The ID of the project in which the resource belongs. If it is not provided, the project will be parsed from the identifier of the parent resource. If no project is provided in the parent identifier and no project is specified, the provider project is used.
member/members- (Required) Identities that will be granted the privilege in
role. Each entry can have one of the following values:
- allUsers: A special identifier that represents anyone who is on the internet; with or without a Google account.
- allAuthenticatedUsers: A special identifier that represents anyone who is authenticated with a Google account or a service account.
- user:[emailid]: An email address that represents a specific Google account. For example, email@example.com or firstname.lastname@example.org.
- serviceAccount:[emailid]: An email address that represents a service account. For example, email@example.com.
- group:[emailid]: An email address that represents a Google group. For example, firstname.lastname@example.org.
- domain:[domain]: A G Suite domain (primary, instead of alias) name that represents all the users of that domain. For example, google.com or example.com.
- projectOwner:projectid: Owners of the given project. For example, "projectOwner:my-example-project"
- projectEditor:projectid: Editors of the given project. For example, "projectEditor:my-example-project"
- projectViewer:projectid: Viewers of the given project. For example, "projectViewer:my-example-project"
role- (Required) The role that should be applied. Only one
google_bigquery_table_iam_bindingcan be used per role. Note that custom roles must be of the format
policy_data- (Required only by
google_bigquery_table_iam_policy) The policy data generated by a
condition block supports:
expression- (Required) Textual representation of an expression in Common Expression Language syntax.
title- (Required) A title for the expression, i.e. a short string describing its purpose.
description- (Optional) An optional description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
Warning: Terraform considers the
roleand condition contents (
expression) as the identifier for the binding. This means that if any part of the condition is changed out-of-band, Terraform will consider it to be an entirely different resource and will treat it as such.
In addition to the arguments listed above, the following computed attributes are exported:
etag- (Computed) The etag of the IAM policy.
Explanation in Terraform Registry
Three different resources help you manage your IAM policy for BigQuery Table. Each of these resources serves a different use case:
google_bigquery_table_iam_policy: Authoritative. Sets the IAM policy for the table and replaces any existing policy already attached.
google_bigquery_table_iam_binding: Authoritative for a given role. Updates the IAM policy to grant a role to a list of members. Other roles within the IAM policy for the table are preserved.
google_bigquery_table_iam_member: Non-authoritative. Updates the IAM policy to grant a role to a new member. Other members for the role for the table are preserved.
google_bigquery_table_iam_policycannot be used in conjunction with
google_bigquery_table_iam_memberor they will fight over what your policy should be.
google_bigquery_table_iam_bindingresources can be used in conjunction with
google_bigquery_table_iam_memberresources only if they do not grant privilege to the same role.
Tips: Best Practices for The Other Google BigQuery Resources
In addition to the google_bigquery_dataset, Google BigQuery has the other resources that should be configured for security reasons. Please check some examples of those resources and precautions.
Ensure your BigQuery dataset blocks unwanted access
It is better to block unwanted access from users outside the organization.