This workshop has been deprecated and archived. The new Amazon EKS Workshop is now available at

In this chapter, we will prepare your EKS cluster so that it is integrated with EMR on EKS. If you don’t have EKS cluster, please review instructions from start the workshop and launch using eksctl modules

Create namespace and RBAC permissions

Let’s create a namespace ‘spark’ in our EKS cluster. After this, we will use the automation powered by eksctl for creating RBAC permissions and for adding EMR on EKS service-linked role into aws-auth configmap

kubectl create namespace spark

eksctl create iamidentitymapping --cluster eksworkshop-eksctl  --namespace spark --service-name "emr-containers"

Enable IAM Roles for Service Account (IRSA)

Your cluster should already have OpenID Connect provider URL. Only configuration that is needed is to associate IAM with OIDC. You can do that by running this command

eksctl utils associate-iam-oidc-provider --cluster eksworkshop-eksctl --approve

Create IAM Role for job execution

Let’s create the role that EMR will use for job execution. This is the role, EMR jobs will assume when they run on EKS.

cat <<EoF > ~/environment/emr-trust-policy.json
  "Version": "2012-10-17",
  "Statement": [
      "Effect": "Allow",
      "Principal": {
        "Service": ""
      "Action": "sts:AssumeRole"

aws iam create-role --role-name EMRContainers-JobExecutionRole --assume-role-policy-document file://~/environment/emr-trust-policy.json

Next, we need to attach the required IAM policies to the role so it can write logs to s3 and cloudwatch.

cat <<EoF > ~/environment/EMRContainers-JobExecutionRole.json
    "Version": "2012-10-17",
    "Statement": [
            "Effect": "Allow",
            "Action": [
            "Resource": "*"
            "Effect": "Allow",
            "Action": [
            "Resource": [
aws iam put-role-policy --role-name EMRContainers-JobExecutionRole --policy-name EMR-Containers-Job-Execution --policy-document file://~/environment/EMRContainers-JobExecutionRole.json

Update trust relationship for job execution role

Now we need to update the trust relationship between IAM role we just created with EMR service identity.

aws emr-containers update-role-trust-policy --cluster-name eksworkshop-eksctl --namespace spark --role-name EMRContainers-JobExecutionRole

Register EKS cluster with EMR

The final step is to register EKS cluster with EMR.

aws emr-containers create-virtual-cluster \
--name eksworkshop-eksctl \
--container-provider '{
    "id": "eksworkshop-eksctl",
    "type": "EKS",
    "info": {
        "eksInfo": {
            "namespace": "spark"

After you register, you should get confirmation that your EMR virtual cluster is created. A virtual cluster is an EMR concept which means that EMR service is registered to Kubernetes namespace and it can run jobs in that namespace.

    "id": "av6h2hk8fsyu12m5ru8zjg8ht",
    "name": "eksworkshop-eksctl",
    "arn": "arn:aws:emr-containers:us-west-2:xxxxxxxxxxxx:/virtualclusters/av6h2hk8fsyu12m5ru8zjg8ht"

Create EKS Managed Node Group

Lets add a EKS managed nodegroup to this EKS cluster to have more resources to run sample spark jobs.

Create a config file (addnodegroup.yaml) with details of a new EKS managed nodegroup.

cat << EOF > addnodegroup.yaml
kind: ClusterConfig

  name: eksworkshop-eksctl
  region: ${AWS_REGION}

- name: emrnodegroup
  desiredCapacity: 3
  instanceType: m5.xlarge
    enableSsm: true


Create the new EKS managed nodegroup.

eksctl create nodegroup --config-file=addnodegroup.yaml

Launching a new EKS managed nodegroup will take a few minutes.

Check if the new nodegroup has been added to your cluster.

kubectl get nodes # if we see 6 nodes in total with the 3 newly added nodes, we know we have authenticated correctly

Let’s create a s3 bucket to upload sample scripts and logs.

export s3DemoBucket=s3://emr-eks-demo-${ACCOUNT_ID}-${AWS_REGION}
aws s3 mb $s3DemoBucket