Manage GCP Vertex AI FeatureGroup IAM Bindings

The gcp:vertex/aiFeatureGroupIamBinding:AiFeatureGroupIamBinding resource, part of the Pulumi GCP provider, manages IAM role bindings for Vertex AI Feature Groups, controlling which identities can access feature data. This guide focuses on two capabilities: granting roles to multiple members and adding individual members to existing roles.

IAM bindings reference existing Feature Groups and require valid GCP project and region configuration. The examples are intentionally small. Combine them with your own Feature Group resources and identity management workflows.

Grant a role to multiple members at once

Teams managing access to Feature Groups often need to grant the same role to multiple users or service accounts simultaneously, such as giving viewer access to a data science team.

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const binding = new gcp.vertex.AiFeatureGroupIamBinding("binding", {
    region: featureGroup.region,
    featureGroup: featureGroup.name,
    role: "roles/viewer",
    members: ["user:jane@example.com"],
});

import pulumi
import pulumi_gcp as gcp

binding = gcp.vertex.AiFeatureGroupIamBinding("binding",
    region=feature_group["region"],
    feature_group=feature_group["name"],
    role="roles/viewer",
    members=["user:jane@example.com"])

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v9/go/gcp/vertex"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := vertex.NewAiFeatureGroupIamBinding(ctx, "binding", &vertex.AiFeatureGroupIamBindingArgs{
			Region:       pulumi.Any(featureGroup.Region),
			FeatureGroup: pulumi.Any(featureGroup.Name),
			Role:         pulumi.String("roles/viewer"),
			Members: pulumi.StringArray{
				pulumi.String("user:jane@example.com"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var binding = new Gcp.Vertex.AiFeatureGroupIamBinding("binding", new()
    {
        Region = featureGroup.Region,
        FeatureGroup = featureGroup.Name,
        Role = "roles/viewer",
        Members = new[]
        {
            "user:jane@example.com",
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureGroupIamBinding;
import com.pulumi.gcp.vertex.AiFeatureGroupIamBindingArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var binding = new AiFeatureGroupIamBinding("binding", AiFeatureGroupIamBindingArgs.builder()
            .region(featureGroup.region())
            .featureGroup(featureGroup.name())
            .role("roles/viewer")
            .members("user:jane@example.com")
            .build());

    }
}

resources:
  binding:
    type: gcp:vertex:AiFeatureGroupIamBinding
    properties:
      region: ${featureGroup.region}
      featureGroup: ${featureGroup.name}
      role: roles/viewer
      members:
        - user:jane@example.com

The AiFeatureGroupIamBinding resource is authoritative for the specified role: it replaces all members for that role with the list you provide. The members array accepts various identity formats including user emails, service accounts, groups, and domains. The featureGroup and region properties identify which Feature Group to bind the role to.

Add a single member to a role incrementally

When onboarding individual users or service accounts, teams often add them one at a time to existing roles without affecting other members who already have access.

import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const member = new gcp.vertex.AiFeatureGroupIamMember("member", {
    region: featureGroup.region,
    featureGroup: featureGroup.name,
    role: "roles/viewer",
    member: "user:jane@example.com",
});

import pulumi
import pulumi_gcp as gcp

member = gcp.vertex.AiFeatureGroupIamMember("member",
    region=feature_group["region"],
    feature_group=feature_group["name"],
    role="roles/viewer",
    member="user:jane@example.com")

package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v9/go/gcp/vertex"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := vertex.NewAiFeatureGroupIamMember(ctx, "member", &vertex.AiFeatureGroupIamMemberArgs{
			Region:       pulumi.Any(featureGroup.Region),
			FeatureGroup: pulumi.Any(featureGroup.Name),
			Role:         pulumi.String("roles/viewer"),
			Member:       pulumi.String("user:jane@example.com"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var member = new Gcp.Vertex.AiFeatureGroupIamMember("member", new()
    {
        Region = featureGroup.Region,
        FeatureGroup = featureGroup.Name,
        Role = "roles/viewer",
        Member = "user:jane@example.com",
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.vertex.AiFeatureGroupIamMember;
import com.pulumi.gcp.vertex.AiFeatureGroupIamMemberArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var member = new AiFeatureGroupIamMember("member", AiFeatureGroupIamMemberArgs.builder()
            .region(featureGroup.region())
            .featureGroup(featureGroup.name())
            .role("roles/viewer")
            .member("user:jane@example.com")
            .build());

    }
}

resources:
  member:
    type: gcp:vertex:AiFeatureGroupIamMember
    properties:
      region: ${featureGroup.region}
      featureGroup: ${featureGroup.name}
      role: roles/viewer
      member: user:jane@example.com

The AiFeatureGroupIamMember resource adds a single identity to a role without modifying existing members. This non-authoritative approach lets you manage access incrementally. Use member (singular) instead of members (plural) to specify the single identity being granted access.

Beyond these examples

These snippets focus on specific IAM binding features: role-based access control and batch and incremental member assignment. They’re intentionally minimal rather than full access management solutions.

The examples reference pre-existing infrastructure such as Vertex AI Feature Groups and GCP project and region configuration. They focus on configuring IAM bindings rather than provisioning Feature Groups themselves.

To keep things focused, common IAM patterns are omitted, including:

Conditional IAM bindings (condition property)
Custom role definitions and formatting
Policy-level management (AiFeatureGroupIamPolicy)
Cross-project or cross-organization access

These omissions are intentional: the goal is to illustrate how IAM bindings are wired, not provide drop-in access control modules. See the AiFeatureGroupIamBinding resource reference for all available configuration options.

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Frequently Asked Questions

Resource Selection & Conflicts

What's the difference between AiFeatureGroupIamPolicy, IamBinding, and IamMember?

AiFeatureGroupIamPolicy is authoritative and replaces the entire IAM policy. AiFeatureGroupIamBinding is authoritative for a single role, replacing all members for that role while preserving other roles. AiFeatureGroupIamMember is non-authoritative, adding one member to a role without affecting other members.

Which IAM resources can I use together?

Don’t use AiFeatureGroupIamPolicy with AiFeatureGroupIamBinding or AiFeatureGroupIamMember, as they’ll conflict. You can use AiFeatureGroupIamBinding with AiFeatureGroupIamMember only if they manage different roles.

Configuration & Identity Formats

What identity formats can I use in the members list?

You can use allUsers, allAuthenticatedUsers, user:{email}, serviceAccount:{email}, group:{email}, domain:{domain}, projectOwner:{projectid}, projectEditor:{projectid}, projectViewer:{projectid}, and federated identities (e.g., principal://iam.googleapis.com/...).

How do I format custom roles?

Custom roles must use the format [projects|organizations]/{parent-name}/roles/{role-name} (e.g., projects/my-project/roles/my-custom-role).

What properties can't be changed after creation?

The featureGroup, role, region, project, and condition properties are immutable and require resource replacement if changed.

Beta & Provider Requirements

Do I need a special provider to use this resource?

Yes, this resource is in beta and requires the terraform-provider-google-beta provider.

Import & Migration

What identifier formats can I use when importing?

You can use projects/{{project}}/locations/{{region}}/featureGroups/{{name}}, {{project}}/{{region}}/{{name}}, {{region}}/{{name}}, or just {{name}}. Variables not provided are taken from the provider configuration.

How do I import an existing IAM binding?

Use space-delimited identifiers: the resource identifier and the role. For example:

pulumi import gcp:vertex/aiFeatureGroupIamBinding:AiFeatureGroupIamBinding editor "projects/{{project}}/locations/{{region}}/featureGroups/{{feature_group}} roles/viewer"

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