Real-time Stream Processing for AI with Amazon EKS and Kafka

Question

Pulumi · Accepted Answer

Real-time stream processing is a powerful pattern used to process and analyze high-volume, high-velocity data without significant delay. To achieve this on AWS, we'll combine several services:

1. **Amazon EKS (Elastic Kubernetes Service)**: This will be used to run our containerized applications. It's a managed Kubernetes service that makes it easier to run Kubernetes on AWS without needing to install and operate your own Kubernetes control plane.

2. **Amazon MSK (Managed Streaming for Apache Kafka)**: This service is used to build and run applications that process streaming data using Apache Kafka. We use MSK because it's fully managed, highly available, and integrates well with AWS services.

3. **A Kafka Client**: In a typical application, you would have a Kafka client that either produces or consumes messages from the Kafka topics. This client can be a microservice running on EKS.

In the program below, we'll create an EKS cluster, an MSK cluster, and set up the necessary networking and IAM roles. We don't configure the Kafka clients in detail, as they would be part of your application code running in containers managed by Kubernetes.

Here's how we can set up these services using Pulumi with Python:

```python
import pulumi
import pulumi_aws as aws

# Create a VPC for our cluster
vpc = aws.ec2.Vpc("vpc", cidr_block="10.100.0.0/16")

# Create subnets for the VPC
subnet = aws.ec2.Subnet("subnet",
                         vpc_id=vpc.id,
                         cidr_block="10.100.1.0/24",
                         availability_zone="us-west-2a")

# Create an IAM role that the EKS service will assume to create AWS resources
eks_role = aws.iam.Role("eksRole", assume_role_policy="""{
     "Version": "2012-10-17",
     "Statement": [
       {
         "Effect": "Allow",
         "Principal": {"Service": "eks.amazonaws.com"},
         "Action": "sts:AssumeRole"
       }
     ]
   }
""")

# Managed policy attachments for the EKS role
eks_policies = ["arn:aws:iam::aws:policy/AmazonEKSWorkerNodePolicy",
                "arn:aws:iam::aws:policy/AmazonEKS_CNI_Policy",
                "arn:aws:iam::aws:policy/AmazonEC2ContainerRegistryReadOnly"]

for policy in eks_policies:
    aws.iam.RolePolicyAttachment(policy,
                                 role=eks_role.id,
                                 policy_arn=policy)

# Create the EKS cluster
eks_cluster = aws.eks.Cluster("eksCluster",
                              role_arn=eks_role.arn,
                              vpc_config=aws.eks.ClusterVpcConfigArgs(
                                  subnet_ids=[subnet.id]
                              ))

# Create an IAM role for the MSK cluster
msk_role = aws.iam.Role("mskRole", assume_role_policy="""{
     "Version": "2012-10-17",
     "Statement": [
       {
         "Effect": "Allow",
         "Principal": {"Service": "kafka.amazonaws.com"},
         "Action": "sts:AssumeRole"
       }
     ]
   }
""")

# Create a security group for the MSK cluster
msk_security_group = aws.ec2.SecurityGroup("mskSecurityGroup",
                                           vpc_id=vpc.id)

# Create the MSK cluster
msk_cluster = aws.msk.Cluster("mskCluster",
                              cluster_name="example-msk-cluster",
                              kafka_version="2.6.1",
                              number_of_broker_nodes=3,
                              broker_node_group_info=aws.msk.ClusterBrokerNodeGroupInfoArgs(
                                  instance_type="kafka.m5.large",
                                  ebs_volume_size=1000,
                                  client_subnets=[subnet.id],
                                  security_groups=[msk_security_group.id]
                              ),
                              roles=[msk_role.arn])

# Export the cluster endpoints to access the clusters
pulumi.export('eks_cluster_endpoint', eks_cluster.endpoint)
pulumi.export('msk_cluster_broker', msk_cluster.bootstrap_brokers)
```

This Pulumi program sets up networking with a VPC and subnet, creates IAM roles with the necessary permissions, sets up an EKS cluster, and creates an MSK cluster within our VPC. The security group for MSK is defined but not elaborated upon; typically, you'd configure this to control traffic to and from your MSK cluster. The roles are assumed by AWS services when managing resources on your behalf.

Make sure you have AWS access configured for Pulumi, either via environment variables, AWS credentials file, or the AWS CLI. This code would then be placed into a Python file (`__main__.py`) in a Pulumi project directory.

To proceed with the deployment, you would run `pulumi up` in your CLI, and Pulumi would execute the code to provision the infrastructure as defined. After the changes are applied, the program exports the EKS cluster endpoint and the MSK cluster broker URLs to access your Kafka streams and Kubernetes API.