Orchestrating AI Workflows with Kubeflow on EKS

Question

Pulumi · Accepted Answer

Orchestrating AI workflows with Kubeflow on Amazon EKS (Elastic Kubernetes Service) can be a complex process that involves several steps. However, Pulumi's infrastructure as code provides a streamlined approach to provision all the resources needed with less manual effort and greater reproducibility. Below is a guide and accompanying Pulumi Python program to help set up an EKS cluster and deploy Kubeflow to orchestrate AI Workflows.

### Guide Overview

1. **Creating an IAM Role for EKS:** This IAM role will provide the necessary permissions for EKS to interact with other AWS services on your behalf.

2. **Setting up the EKS Cluster:** Provision an Elastic Kubernetes Service (EKS) cluster, which is the managed Kubernetes service by AWS.

3. **Defining EKS Node Groups:** Define the worker nodes for the cluster. These nodes are where your Kubeflow pipelines and AI workloads will run.

4. **Deploying Kubeflow:** Once our EKS cluster is set up, you would typically use `kubectl` to apply Kubeflow manifests; however, this step is beyond Pulumi's scope and is typically done with configuration management tools or manually.

### Assumptions
- AWS credentials are configured either via the AWS CLI or Pulumi configuration.
- Kubeflow installation details, such as specific version or any customization, are provided as per user requirements.

### Prerequisites
- Pulumi CLI installed and configured.
- Python (version 3.x) installed.
- AWS CLI installed and configured with appropriate access.
  
### Python Program Description
The following program will create a simple EKS cluster, ready to deploy Kubeflow on it. We will use the `pulumi_eks` library, which simplifies the process of creating EKS clusters.

```python
import pulumi
import pulumi_aws as aws
import pulumi_eks as eks

# Step 1: Creating an IAM Role for the EKS Cluster
eks_role = aws.iam.Role("eksRole",
    assume_role_policy="""{
        "Version": "2012-10-17",
        "Statement": [{
            "Action": "sts:AssumeRole",
            "Effect": "Allow",
            "Principal": {
                "Service": "eks.amazonaws.com"
            }
        }]
    }""")

# Attach necessary policies for the EKS cluster
eks_policy_arns = [
    "arn:aws:iam::aws:policy/AmazonEKSClusterPolicy",
    "arn:aws:iam::aws:policy/AmazonEKSServicePolicy"
]

for policy_arn in eks_policy_arns:
    aws.iam.RolePolicyAttachment(f"eksRolePolicyAttachment-{policy_arn}",
        role=eks_role.name,
        policy_arn=policy_arn)

# Step 2: Setting up the EKS Cluster
# Assuming an existing VPC and subnets setup
vpc_id = "vpc-12345678"
public_subnet_ids = ["subnet-0123456789abcdef0", "subnet-0123456789abcdef1"]

# Creating the EKS cluster
eks_cluster = eks.Cluster("eksCluster",
    role_arn=eks_role.arn,
    vpc_id=vpc_id,
    public_subnet_ids=public_subnet_ids,
    instance_type="m5.large",
    desired_capacity=2,
    min_size=1,
    max_size=3)

# Step 3: Defining EKS Node Groups
node_group = eks_cluster.create_node_group("eksNodeGroup",
    instance_type="m5.large",
    desired_capacity=2,
    min_size=1,
    max_size=3)

# Exporting the kubeconfig to access the cluster
kubeconfig = eks_cluster.kubeconfig.apply(lambda kc: kc.raw_config)

pulumi.export('kubeconfig', kubeconfig)
```

### Key Resource Explanations

- **IAM Role (eks.Role):** Creates an AWS IAM Role with the necessary trust relationship allowing EKS to assume it.

- **Role Policy Attachments (iam.RolePolicyAttachment):** Attaches the necessary AWS managed policies to the IAM role created for EKS to function correctly.

- **EKS Cluster (eks.Cluster):** Provisions an EKS cluster with the specified characteristics such as VPC, subnets, and node groups.

- **Node Group:** A group of EC2 instances that are registered with the EKS cluster as worker nodes.

### Deploying the Program
To deploy this program, you would run `pulumi up` in the terminal within the directory where this program is saved. Review the plan that Pulumi presents and then select 'yes' to commence provisioning these resources in AWS.

After setting up the cluster, you would proceed with Kubeflow deployment which involves obtaining Kubeflow manifests and using `kubectl apply` to set up various components on the EKS cluster. This step would normally be managed outside of Pulumi, as Pulumi is focused on provisioning the underlying infrastructure required.