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. It grants a specific role to a list of members authoritatively, meaning it controls all members for that role while preserving other roles on the Feature Group. This guide focuses on two capabilities: granting roles to multiple members and adding individual members non-authoritatively.

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

Grant a role to multiple members at once

Teams managing Feature Group access often grant the same role to multiple users or service accounts simultaneously, such as giving viewer access to an entire 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 members array lists all identities that receive the specified role. The binding is authoritative for this role, replacing any previous member list for roles/viewer. The featureGroup and region properties identify which Feature Group to bind. Member identities can be users, service accounts, groups, or special identifiers like allAuthenticatedUsers.

Add a single member to an existing role

When onboarding individual users, the non-authoritative member resource adds one identity without affecting others who already have the same role.

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 member property specifies a single identity to grant the role. Unlike AiFeatureGroupIamBinding, this resource is non-authoritative: it adds the member without removing existing members for the same role. Use this when you need incremental access grants without managing the complete member list.

Beyond these examples

These snippets focus on specific IAM binding features: role-based access control and batch 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)
Policy-level management (AiFeatureGroupIamPolicy)
Custom role definitions
Cross-project or organization-level bindings

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 specific role, preserving other roles. AiFeatureGroupIamMember is non-authoritative, adding a single member while preserving other members for that role.

Can I use these IAM resources together?

AiFeatureGroupIamPolicy cannot be used with AiFeatureGroupIamBinding or AiFeatureGroupIamMember, as they will conflict. However, AiFeatureGroupIamBinding and AiFeatureGroupIamMember can be used together only if they manage different roles.

How do I grant a role to multiple users at once?

Use AiFeatureGroupIamBinding with the members property set to an array of identities, such as ["user:jane@example.com", "user:john@example.com"].

IAM Configuration

What format do custom roles require?

Custom roles must use the format [projects|organizations]/{parent-name}/roles/{role-name}, for example projects/my-project/roles/my-custom-role.

What member identity formats are supported?

Supported formats include allUsers, allAuthenticatedUsers, user:{email}, serviceAccount:{email}, group:{email}, domain:{domain}, projectOwner:{projectid}, projectEditor:{projectid}, projectViewer:{projectid}, and federated identities like principal://iam.googleapis.com/....

Immutability & Lifecycle

What properties are immutable after creation?

The featureGroup, role, region, project, and condition properties cannot be changed after the resource is created.

How do I import an existing IAM binding?

Use the format

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

. For custom roles, use the full role name including the project or organization prefix.

Using a different cloud?

Explore security guides for other cloud providers:

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