Phase 6: Cloud Deployment in Client Environments · 55 min · Python · Kubernetes · GKE

Private Kubernetes & Workload Identity

No public API endpoint. No static credentials. No exceptions.

Hiring signal: System design interviews test Kubernetes security: candidates who deploy private GKE/EKS clusters with private control planes, use Workload Identity instead of static credentials, and configure network policies for pod isolation pass. Candidates who expose the K8s API to the internet or use hardcoded service account keys fail. GPU node pool configuration for inference workloads is a bonus signal.

What you will learn

Deploy private GKE clusters: private control plane, private nodes, authorized networks
Configure Workload Identity: binding K8s service accounts to cloud IAM, eliminating static credentials
Deploy EKS private clusters: private API server, VPC endpoints
Configure node pools: GPU nodes for inference, CPU nodes for orchestration, autoscaling
Implement network policies: restricting pod-to-pod communication, egress controls, namespace isolation

What You'll Learn

This lesson takes approximately 55 min. By the end, you will be able to:

Deploy private GKE clusters: private control plane, private nodes, authorized networks
Configure Workload Identity: binding K8s service accounts to cloud IAM, eliminating static credentials
Deploy EKS private clusters: private API server, VPC endpoints
Configure node pools: GPU nodes for inference, CPU nodes for orchestration, autoscaling
Implement network policies: restricting pod-to-pod communication, egress controls, namespace isolation

The Problem

Private Kubernetes clusters — with no public API endpoint — are the standard for enterprise AI deployments. You access them through a bastion host, VPN, or private peering. Workload identity replaces static credentials with short-lived tokens from the cloud IAM. This lesson covers private cluster architecture and workload identity configuration.

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers Private GKE Cluster with Terraform, Workload Identity: K8s Service Account to GCP IAM, EKS Private Cluster with VPC Endpoints, Network Policies: Pod-to-Pod Isolation, Practical Application, What Hiring Managers Look For, Resources, Key Takeaways, Next Steps — plus a hands-on lab, quiz, and project artifact.

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