Manage GCP Vertex AI Feature Store Entity Type IAM Bindings

The gcp:vertex/aiFeatureStoreEntityTypeIamBinding:AiFeatureStoreEntityTypeIamBinding resource, part of the Pulumi GCP provider, manages IAM role bindings for Vertex AI Featurestore EntityTypes, controlling which identities can access feature data. This guide focuses on two capabilities: authoritative role binding for multiple members and non-authoritative member addition.

IAM bindings reference existing Featurestore and EntityType resources. The examples are intentionally small. Combine them with your own Featurestore infrastructure and identity management strategy.

Grant a role to multiple members at once

When managing feature store access, you 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.AiFeatureStoreEntityTypeIamBinding("binding", {
    featurestore: entity.featurestore,
    entitytype: entity.name,
    role: "roles/viewer",
    members: ["user:jane@example.com"],
});

import pulumi
import pulumi_gcp as gcp

binding = gcp.vertex.AiFeatureStoreEntityTypeIamBinding("binding",
    featurestore=entity["featurestore"],
    entitytype=entity["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.NewAiFeatureStoreEntityTypeIamBinding(ctx, "binding", &vertex.AiFeatureStoreEntityTypeIamBindingArgs{
			Featurestore: pulumi.Any(entity.Featurestore),
			Entitytype:   pulumi.Any(entity.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.AiFeatureStoreEntityTypeIamBinding("binding", new()
    {
        Featurestore = entity.Featurestore,
        Entitytype = entity.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.AiFeatureStoreEntityTypeIamBinding;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeIamBindingArgs;
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 AiFeatureStoreEntityTypeIamBinding("binding", AiFeatureStoreEntityTypeIamBindingArgs.builder()
            .featurestore(entity.featurestore())
            .entitytype(entity.name())
            .role("roles/viewer")
            .members("user:jane@example.com")
            .build());

    }
}

resources:
  binding:
    type: gcp:vertex:AiFeatureStoreEntityTypeIamBinding
    properties:
      featurestore: ${entity.featurestore}
      entitytype: ${entity.name}
      role: roles/viewer
      members:
        - user:jane@example.com

The binding 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 special identifiers like allAuthenticatedUsers. The featurestore and entitytype properties identify which EntityType resource receives the binding.

Add a single member to a role incrementally

When onboarding individual users or service accounts, you can add them 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.AiFeatureStoreEntityTypeIamMember("member", {
    featurestore: entity.featurestore,
    entitytype: entity.name,
    role: "roles/viewer",
    member: "user:jane@example.com",
});

import pulumi
import pulumi_gcp as gcp

member = gcp.vertex.AiFeatureStoreEntityTypeIamMember("member",
    featurestore=entity["featurestore"],
    entitytype=entity["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.NewAiFeatureStoreEntityTypeIamMember(ctx, "member", &vertex.AiFeatureStoreEntityTypeIamMemberArgs{
			Featurestore: pulumi.Any(entity.Featurestore),
			Entitytype:   pulumi.Any(entity.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.AiFeatureStoreEntityTypeIamMember("member", new()
    {
        Featurestore = entity.Featurestore,
        Entitytype = entity.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.AiFeatureStoreEntityTypeIamMember;
import com.pulumi.gcp.vertex.AiFeatureStoreEntityTypeIamMemberArgs;
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 AiFeatureStoreEntityTypeIamMember("member", AiFeatureStoreEntityTypeIamMemberArgs.builder()
            .featurestore(entity.featurestore())
            .entitytype(entity.name())
            .role("roles/viewer")
            .member("user:jane@example.com")
            .build());

    }
}

resources:
  member:
    type: gcp:vertex:AiFeatureStoreEntityTypeIamMember
    properties:
      featurestore: ${entity.featurestore}
      entitytype: ${entity.name}
      role: roles/viewer
      member: user:jane@example.com

The member resource is non-authoritative: it adds one identity to a role without removing existing members. This approach works well for incremental access grants where you don’t want to manage the complete member list. You can combine multiple member resources for the same role, or mix member resources with binding resources as long as they target different roles.

Beyond these examples

These snippets focus on specific IAM binding features: role-based access control and authoritative vs non-authoritative member management. They’re intentionally minimal rather than complete access control configurations.

The examples reference pre-existing infrastructure such as Vertex AI Featurestore and EntityType resources. They focus on configuring IAM bindings rather than provisioning the underlying feature store.

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

Conditional IAM bindings (condition property)
Policy resource for complete IAM replacement
Custom role definitions and formatting
Federated identity and workload identity pool configuration

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

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Frequently Asked Questions

Resource Selection & Conflicts

What's the difference between IamPolicy, IamBinding, and IamMember resources?

AiFeatureStoreEntityTypeIamPolicy is fully authoritative and replaces the entire IAM policy. AiFeatureStoreEntityTypeIamBinding is authoritative for a single role, managing all members for that role while preserving other roles. AiFeatureStoreEntityTypeIamMember is non-authoritative, adding individual members without affecting other members or roles.

Can I use IamPolicy together with IamBinding or IamMember?

No, AiFeatureStoreEntityTypeIamPolicy cannot be used with AiFeatureStoreEntityTypeIamBinding or AiFeatureStoreEntityTypeIamMember because they will conflict over the policy state.

Can I use IamBinding and IamMember together?

Yes, but only if they don’t grant privileges to the same role. Using both for the same role causes conflicts.

Configuration & Identity Management

What member identity formats are supported?

Supported formats include user:{email}, serviceAccount:{email}, group:{email}, domain:{domain}, projectOwner/Editor/Viewer:{projectid}, allUsers, allAuthenticatedUsers, and federated identities using principal:// URIs.

Custom Roles & Advanced Usage

How do I specify a custom role?

Custom roles must use the full path format: projects/{project}/roles/{role-name} or organizations/{org}/roles/{role-name}. This is especially important when importing IAM resources.

Using a different cloud?

Explore security guides for other cloud providers:

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