In Part 2, the focus shifts to deploying worker nodes for an EKS cluster, a crucial step after setting up the control plane. Worker nodes are essentially EC2 instances configured to run Kubernetes workloads, requiring agents like kubelet and a container runtime. AWS offers three deployment models: Managed Nodes, Self-managed Nodes, and AWS Fargate, each with varying levels of control and operational cost. Managed Node Groups, the method explored in this part, offer a practical balance by partially managing infrastructure for the user.
This approach simplifies deployment by automating the creation of Auto Scaling Groups, selection of EKS-Optimized AMIs, and configuration for cluster joining. It also handles node authorization mapping and provides built-in upgrade workflows. The process involves creating an IAM role for worker nodes with specific policies, then configuring a Managed Node Group within the EKS console, specifying instance details and private subnets.
Behind the scenes, AWS provisions an Auto Scaling Group, a Launch Template, and security groups for the worker nodes. The nodes authenticate to the Kubernetes API server using their IAM role, which is then mapped to a Kubernetes identity via the `aws-auth` ConfigMap or access entries. Successful node registration is verified by checking the output of `kubectl get nodes`. Common issues include incorrect IAM roles, missing policies, subnet misconfigurations, capacity shortages, and DNS resolution problems. The next part will delve into EKS networking concepts.
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