Kubernetes Infrastructure & AWS EKS

Container Orchestration at Scale

Comprehensive exploration of Kubernetes from local development with Minikube to production-grade deployments on AWS EKS. Hands-on projects demonstrating scalable, resilient container orchestration for machine learning and cloud-native applications.

Minikube vs AWS EKS

Understanding the Kubernetes deployment spectrum from local development to cloud production

Minikube – Local Development

Single-node Kubernetes cluster for local development, testing, and learning Kubernetes fundamentals.

  • Environment: Local machine with Docker Desktop
  • Use Case: Development, Testing, Learning Kubernetes
  • Scaling: Single node only
  • Networking: Local tunneling with minikube service
  • Cost: Free (local resources only)

AWS EKS – Production

Managed Kubernetes service for production workloads with high availability, auto-scaling, and enterprise features.

  • Environment: AWS Cloud with managed control plane
  • Use Case: Production, High Availability, Enterprise
  • Scaling: Multi-node, auto-scaling, multi-AZ
  • Networking: AWS Load Balancer, VPC integration
  • Cost: Pay-per-use + EC2/node costs

Hands-On Kubernetes Projects

Structured learning through practical implementation across development and production environments

Minikube Single Pod Architecture Local K8S

Minikube – Single Pod Deployment

Local Kubernetes setup with Minikube for single-pod application deployment, service exposure, and local tunneling for testing.

Core Implementation
  • Minikube Cluster Setup: minikube start, minikube status
  • Pod Deployment: Single-container pod with YAML configuration
  • Service Exposure: NodePort service for local access
  • Local Tunneling: minikube service <service-name> for external access
  • Namespace Management: Creating and managing Kubernetes namespaces
Technologies Used
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Minikube Multi-Pod Architecture Advanced Local

Minikube – Multi-Pod & Scaling

Advanced local Kubernetes deployment with multiple pods, replica scaling, rolling updates, and rollout strategies.

Advanced Features
  • Deployment Management: Deployment objects with replica scaling
  • Rolling Updates: Zero-downtime deployment updates with kubectl rollout
  • Health Checks: Readiness and liveness probes for pod health
  • Resource Limits: CPU and memory constraints per pod
  • Configuration Management: ConfigMaps and Secrets for environment configuration
Technologies Used
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AWS EKS ML Deployment Architecture Production

AWS EKS – Production ML Deployment

Production-grade machine learning model deployment on AWS EKS with load balancing, auto-scaling, and cloud monitoring.

Production Features
  • AWS EKS Cluster: Managed Kubernetes with eksctl cluster creation
  • Load Balancing: AWS Application Load Balancer integration
  • Auto-scaling: Cluster and pod auto-scaling based on load
  • IAM Integration: AWS IAM roles for service accounts (IRSA)
  • Monitoring: CloudWatch metrics and logging integration
Technologies Used
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AWS EKS Deep Dive

Comprehensive understanding of production Kubernetes on AWS

IAM & Security

  • IAM roles for service accounts (IRSA)
  • Security groups and network policies
  • Secrets management with AWS Secrets Manager
  • Pod security standards and compliance
  • AWS KMS for encryption at rest

Networking & Load Balancing

  • VPC CNI plugin for pod networking
  • AWS Load Balancer Controller
  • Ingress resources with ALB/NLB
  • Service mesh options (App Mesh, Istio)
  • Cross-zone load balancing

Operations & Monitoring

  • Cluster auto-scaling with Karpenter
  • CloudWatch metrics and logs
  • Prometheus and Grafana integration
  • Backup and disaster recovery strategies
  • Cost optimization and resource management

Ready to implement scalable Kubernetes solutions for your machine learning or cloud-native applications? Let's discuss production-ready container orchestration strategies.

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