Now we have everything in place to create and manage EC2 instances that will serve as our worker nodes in the Kubernetes cluster. This setup uses an EC2 AutoScaling Group (ASG) rather than manually working with EC2 instances. This offers flexibility to scale up and down the worker nodes on demand when used in conjunction with AutoScaling policie…

terraform_ec2.tf

data "aws_ami" "eks-worker" {
   filter {
     name   = "name"
     values = ["amazon-eks-node-${aws_eks_cluster.demo.version}-v*"]
   }

   most_recent = true
   owners      = ["602401143452"] # Amazon EKS AMI Account ID
 }

# This data source is included for ease of sample architecture deployment
# and can be swapped out as necessary.
data "aws_region" "current" {
}

# EKS currently documents this required userdata for EKS worker nodes to
# properly configure Kubernetes applications on the EC2 instance.
# We implement a Terraform local here to simplify Base64 encoding this
# information into the AutoScaling Launch Configuration.
# More information: https://docs.aws.amazon.com/eks/latest/userguide/launch-workers.html
locals {
  demo-node-userdata = <<USERDATA
#!/bin/bash
set -o xtrace
/etc/eks/bootstrap.sh --apiserver-endpoint '${aws_eks_cluster.demo.endpoint}' --b64-cluster-ca '${aws_eks_cluster. demo.certificate_authority[0].data}' '${var.cluster-name}'
USERDATA

}

resource "aws_launch_configuration" "demo" {
  associate_public_ip_address = true
  iam_instance_profile        = aws_iam_instance_profile.demo-node.name
  image_id                    = data.aws_ami.eks-worker.id
  instance_type               = "m4.large"
  name_prefix                 = "terraform-eks-demo"
  security_groups  = [aws_security_group.demo-node.id]
  user_data_base64 = base64encode(local.demo-node-userdata)

  lifecycle {
    create_before_destroy = true
  }
}