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Amazon EKS 0.65.5Last updated in version 0.64.3

EKS K8S Role Mapping Module

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NOTE: This module manages a single ConfigMap to use with Kubernetes AWS IAM authentication. If you wish to break up the ConfigMap across multiple smaller ConfigMaps to manage entries in isolated modules (e.g., when you add a new IAM role in a separate module from the EKS cluster), refer to the eks-aws-auth-merger.

This Module can be used to manage the mapping of AWS IAM roles and users to Kubernetes RBAC groups for finer grained access control of your EKS Cluster.

This Module only manages the mapping between IAM roles and Kubernetes RBAC groups. This Module does not create, modify, or configure either roles. We recommend managing them in a separate Terraform template in the context of your needs, that are then provided as inputs to this module.

What is Kubernetes Role Based Access Control (RBAC)?

Role Based Access Control (RBAC) is a method to regulate access to resources based on the role that individual users assume in an organization. Kubernetes allows you to define roles in the system that individual users inherit, and explicitly grant permissions to resources within the system to those roles. The Control Plane will then honor those permissions when accessing the resources on Kubernetes on behalf of clients such as kubectl. When combined with namespaces, you can implement sophisticated control schemes that limit the access of resources across the roles in your organization.

The RBAC system is managed using ClusterRole and ClusterRoleBinding resources (or Role and RoleBinding resources if restricting to a single namespace). The ClusterRole (or Role) object defines a role in the Kubernetes system that has explicit permissions on what it can and cannot do. These roles are then bound to users and groups using the ClusterRoleBinding (or RoleBinding) resource. An important thing to note here is that you do not explicitly create users and groups using RBAC, and instead rely on the authentication system to implicitly create these entities.

You can refer to the example scenarios below for an example of this in action.

Refer to the official documentation for more information.

What is an AWS IAM role?

AWS IAM role is AWS's implementation of RBAC. Users and clients authenticate to AWS to assume an IAM role, that has a set of permissions that grant or deny access to various resources within AWS. Unlike users, IAM roles do not have long standing credentials associated with them. Instead, a user uses the AWS API to assume a role, which will issue temporary credentials that can be used to access the AWS resources as the assumed role. Like the roles in the Kubernetes RBAC implementation, you can configure the roles to have as much or as little permissions as necessary when accessing resources in the AWS system.

This Module provides code for you to manage the mapping between AWS IAM roles and Kubernetes RBAC roles so that you can maintain a consistent set of mappings between the two systems. This works hand in hand with the EKS authentication system, providing the information to Kubernetes to resolve the user to the right RBAC group based on the provided IAM role credentials.

Examples

Restricting specific actions

Suppose that you are setting up your EKS cluster for your organization that has an ops team and a dev team. Suppose further that your organization would like to restrict access to your dev team so that they can only list and update existing Pods, but can not create new ones, while the ops team is able to manage all resources in your Kubernetes cluster.

To support this, we need to first define the roles in Kubernetes that map to the explicit permissions granted to each team. For the ops team in Kubernetes, since we want to grant them admin level privileges on the cluster, we can use the default system:admin group that will already obtain those permissions. For the dev group however, there is no default group and role that fits our needs, so we need to define a new ClusterRole and bind it to the dev group. To do this, we will first define the ClusterRole resource using the RBAC API:

# dev-role.yml
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: dev
rules:
- apiGroups: [""]
resources: ["pods"]
verbs: ["get", "list", "update"]

This creates a new role dev that allows the role to get, list, and update Pods in any namespace in the cluster. We can apply this on the cluster using kubectl:

kubectl apply -f dev-role.yml

We then need to bind this to the dev group using a ClusterRoleMapping resource:

# dev-role-binding.yml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: bind-dev
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: dev
subjects:
- kind: Group
name: dev
apiGroup: rbac.authorization.k8s.io

This config binds the ClusterRole named dev to the Group named dev. Like the ClusterRole config, we can apply this on the cluster using kubectl:

kubectl apply -f dev-role-binding.yml

Now that we have the two roles and bindings in the system, we need some way for users in the ops and dev teams to inherit the roles. This is done implicitly by mapping their authentication credentials to their respective groups. In EKS, authentication is handled by IAM, which means that we need to tell Kubernetes to map their IAM credentials to their respective groups. We will use this Module to do exactly that.

This Module takes as input a mapping between IAM roles and RBAC groups as part of the iam_role_to_rbac_group_mapping input variable. In this example, we will assume that members of the ops team access the cluster by assuming the ops IAM role and members of the dev team access the cluster by assuming the dev IAM role, so we will map these to their respective groups in Kubernetes:

module "eks_k8s_role_mapping" {
eks_worker_iam_role_arn = "arn.aws.iam::5555555555:role/eks-worker"

iam_role_to_rbac_group_mappings = "${
map(
"arn:aws:iam::555555555555:role/dev", list("dev"),
"arn:aws:iam::555555555555:role/ops", list("system:admin"),
)
}"
}

When you terraform apply the above code, the Module will configure Kubernetes to resolve the provided AWS IAM roles to the specified RBAC groups when fulfilling client requests. In this case, any kubectl authentications using the dev IAM role will resolve to the dev Kubernetes RBAC group, while any authentications using the ops IAM role will resolve to the system:admin Kubernetes RBAC group. The dev team will then implicitly inherit the dev ClusterRole based on the ClusterRoleBinding that binds that role to the dev group.

Important: Note that we did not need to define the dev group explicitly in Kubernetes. This is automatically handled by the authentication system. In Kubernetes, the group is implicitly defined as part of defining a user entity that can map to it. As such, it is important to take care to avoid typos here to ensure that the string you use for the group here matches any groups referenced in the role bindings.

Restricting by namespace

In this example, suppose that you are setting up a dev EKS cluster for your dev team that is organized into multiple subteams working on different products. In this scenario, you want to give members of the dev team full access to deploy and manage their applications, including deleting resources. However, you may want to implement controls so that teams can only manage their own resources, and not others' resources.

To support this, you would use Kubernetes namespaces to partition your Kubernetes cluster. Namespaces allow you to divide your resources into logical groups on the cluster. By utilizing namespaces, you can grant teams full access to resources launched in their own namespace, but restrict access to resources in other namespaces.

To implement this on your EKS cluster, you would first need to create namespaces for each team. For this example, we will assume there are two dev teams in the organization: api and backend. So we will create a namespace for each team:

# namespaces.yml
---
kind: Namespace
apiVersion: v1
metadata:
name: apiteam
labels:
name: apiteam
---
kind: Namespace
apiVersion: v1
metadata:
name: backendteam
labels:
name: backendteam

This will create two namespaces: one named apiteam and one named backendteam. We can apply this on the cluster using kubectl:

kubectl apply -f namespaces.yml

Next, we need to create RBAC roles in Kubernetes that grant access to each of the namespaces, but not others. To do this we will rely on the Role resource, instead of the ClusterRole resource because we want to scope the permissions to a particular namespace:

# roles.yml
---
kind: Role
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
name: apiteam-full-access
namespace: apiteam
rules:
- apiGroups: ["", "extensions", "apps"]
resources: ["*"]
verbs: ["*"]
---
kind: Role
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
name: backendteam-full-access
namespace: backendteam
rules:
- apiGroups: ["", "extensions", "apps"]
resources: ["*"]
verbs: ["*"]

This will create two roles in the Kubernetes cluster: apiteam-full-access and backendteam-full-access, each giving full access to all resources in the respective namespaces. Like the YAML file for the namespaces, you can apply this on the cluster using kubectl:

kubectl apply -f roles.yml

To allow authenticating entities to be able to inherit these roles, we need to map these to a group. We can do that by defining RoleBinding resources:

# role-bindings.yml
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: bind-apiteam
namespace: apiteam
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: apiteam-full-access
subjects:
- kind: Group
name: apiteam
apiGroup: rbac.authorization.k8s.io
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: bind-backendteam
namespace: backendteam
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: backendteam-full-access
subjects:
- kind: Group
name: backendteam
apiGroup: rbac.authorization.k8s.io

These two resources bind the apiteam to the apiteam-full-access role and the backendteam to the backendteam-full-access role so that any client that maps to those groups will inherit the right permissions. We can apply this to the cluster using kubectl:

kubectl apply -f role-bindings.yml

Now that we have the namespaces, the roles, and the bindings in the system, we need to create the AWS IAM roles that map to each team and tell Kubernetes to map the AWS IAM role to the proper RBAC role when authenticating the client. We will assume that the IAM roles already exist (named ApiDeveloper and BackendDeveloper). To map the IAM roles to the RBAC groups, we will use this Module. This Module takes as input a mapping between IAM roles and RBAC roles as part of the iam_role_to_rbac_group_mapping input variable:

module "eks_k8s_role_mapping" {
eks_worker_iam_role_arn = "arn.aws.iam::5555555555:role/eks-worker"

iam_role_to_rbac_group_mappings = "${
map(
"arn:aws:iam::555555555555:role/ApiDeveloper", list("apiteam"),
"arn:aws:iam::555555555555:role/BackendDeveloper", list("backendteam"),
)
}"
}

When you terraform apply the above code, the Module will configure Kubernetes to resolve the provided AWS IAM roles to the specified RBAC groups when fulfilling client requests. In this case, any kubectl authentications using the ApiDeveloper IAM role will resolve to the apiteam Kubernetes RBAC group, while any authentications using the BackendDeveloper IAM role will resolve to the backendteam Kubernetes RBAC group. In this way, the developers who authenticate as ApiDeveloper will only be able to access the apiteam namespace in the Kubernetes cluster, while the developers who authenticate as BackendDeveloper will only be able to access the backendteam namespace.

Important: Note that we did not need to define the apiteam and backendteam group explicitly in Kubernetes. This is automatically handled by the authentication system. In Kubernetes, the group is implicitly defined as part of defining a user entity that can map to it. As such, it is important to take care to avoid typos here to ensure that the string you use for the group here matches any groups referenced in the role bindings.

Why not use a Helm Chart?

This Module cannot be implemented as a helm chart due to the functionality of the ConfigMap being generated here. In EKS, the worker nodes also use an IAM role to authenticate against the EKS Control Plane. As such, the worker nodes rely on the mapping from the aws-auth ConfigMap generated by this module to be able to successfully register to the EKS cluster as a worker node.

To use Helm, the Kubernetes cluster must be running the Tiller (Helm Server) Pods on the cluster. However, to run the Tiller Pods, the cluster must have worker nodes online and available. As such, we have a chicken and egg situation, where to use Helm we need to have worker nodes, which need the aws-auth ConfigMap, which needs Helm.

To avoid this cyclic dependency, we implement this module using the kubernetes provider which will use kubectl under the hood. The cluster requirement for a working kubectl is the EKS control plane, which will be available without the ConfigMap and as such does not have the cyclic dependency problem of Helm.

Sample Usage

main.tf

# ------------------------------------------------------------------------------------------------------
# DEPLOY GRUNTWORK'S EKS-K8S-ROLE-MAPPING MODULE
# ------------------------------------------------------------------------------------------------------

module "eks_k_8_s_role_mapping" {

source = "git::git@github.com:gruntwork-io/terraform-aws-eks.git//modules/eks-k8s-role-mapping?ref=v0.65.5"

# ----------------------------------------------------------------------------------------------------
# REQUIRED VARIABLES
# ----------------------------------------------------------------------------------------------------

# List of AWS ARNs of the IAM roles associated with the EKS worker nodes. Each
# IAM role passed in will be set up as a Node role in Kubernetes.
eks_worker_iam_role_arns = <list(string)>

# ----------------------------------------------------------------------------------------------------
# OPTIONAL VARIABLES
# ----------------------------------------------------------------------------------------------------

# Map of string keys and values that can be used to tag the ConfigMap resource
# that holds the mapping information.
config_map_labels = {}

# List of AWS ARNs of the IAM roles associated with launching fargate pods.
# Each IAM role passed in will be set up as a Node role in Kubernetes.
eks_fargate_profile_executor_iam_role_arns = []

# Mapping of AWS IAM roles to RBAC groups, where the keys are AWS ARN of IAM
# roles and values are the mapped k8s RBAC group names as a list.
iam_role_to_rbac_group_mappings = {}

# Mapping of AWS IAM roles assumed via SSO (IAM Identity Center) to RBAC
# groups, where the keys are AWS ARN of IAM role and values are the mapped k8s
# RBAC group names as a list.
iam_sso_role_to_rbac_group_mappings = {}

# Mapping of AWS IAM users to RBAC groups, where the keys are AWS ARN of IAM
# users and values are the mapped k8s RBAC group names as a list.
iam_user_to_rbac_group_mappings = {}

# Name to apply to the ConfigMap that is created. Note that this must be
# called aws-auth, unless you are using the aws-auth-merger.
name = "aws-auth"

# Namespace to create the ConfigMap in. Note that this must be kube-system,
# unless you are using the aws-auth-merger.
namespace = "kube-system"

}


Reference

Required

eks_worker_iam_role_arnslist(string)required

List of AWS ARNs of the IAM roles associated with the EKS worker nodes. Each IAM role passed in will be set up as a Node role in Kubernetes.

Optional

config_map_labelsmap(string)optional

Map of string keys and values that can be used to tag the ConfigMap resource that holds the mapping information.

{}

List of AWS ARNs of the IAM roles associated with launching fargate pods. Each IAM role passed in will be set up as a Node role in Kubernetes.

[]
iam_role_to_rbac_group_mappingsmap(list(…))optional

Mapping of AWS IAM roles to RBAC groups, where the keys are AWS ARN of IAM roles and values are the mapped k8s RBAC group names as a list.

map(list(string))
{}

Mapping of AWS IAM roles assumed via SSO (IAM Identity Center) to RBAC groups, where the keys are AWS ARN of IAM role and values are the mapped k8s RBAC group names as a list.

map(list(string))
{}
iam_user_to_rbac_group_mappingsmap(list(…))optional

Mapping of AWS IAM users to RBAC groups, where the keys are AWS ARN of IAM users and values are the mapped k8s RBAC group names as a list.

map(list(string))
{}
namestringoptional

Name to apply to the ConfigMap that is created. Note that this must be called aws-auth, unless you are using the aws-auth-merger.

"aws-auth"
namespacestringoptional

Namespace to create the ConfigMap in. Note that this must be kube-system, unless you are using the aws-auth-merger.

"kube-system"