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Enterprise Architecture

This guide covers architectural patterns and best practices for designing and managing large-scale Kubernetes deployments across AWS, Azure, and GCP.

Multi-Cluster Architecture Models

Hub and Spoke Model

The hub cluster centrally manages configuration, security policies, and observability for multiple spoke clusters.

                     ┌──────────────┐
                     │  Hub Cluster │
                     │  (Admin/Mgmt)│
                     └───────┬──────┘
                             │
           ┌─────────────────┼─────────────────┐
           │                 │                 │
    ┌──────▼──────┐   ┌──────▼──────┐   ┌──────▼──────┐
    │ Spoke       │   │ Spoke       │   │ Spoke       │
    │ (Workload)  │   │ (Workload)  │   │ (Workload)  │
    └─────────────┘   └─────────────┘   └─────────────┘

Real-life example: Financial services organization with regulated workloads in separate clusters but unified governance.

Multi-Regional Architecture

Independent cluster instances deployed across regions for data sovereignty and resilience.

Real-life example: Global SaaS provider maintaining regional data residency while providing uniform service.

Cloud-Specific Implementation Patterns

AWS EKS Architecture

Best Practices:

  • Use EKS add-ons for CNI, CoreDNS, and kube-proxy

  • Leverage AWS Load Balancer Controller for ALB/NLB integration

  • Use Node Groups with Auto Scaling Groups

  • Implement dedicated VPC endpoints for ECR, S3, and other AWS services

  • Configure AWS IAM for Kubernetes RBAC integration

Real-life considerations:

  • ALB for ingress offers native integrations with AWS WAF and Shield

  • Use Cluster Autoscaler with multiple node groups for cost optimization

  • Auto-scaling with Karpenter provides faster node provisioning

Azure AKS Architecture

Best Practices:

  • Enable managed identity and RBAC integration

  • Implement Azure CNI networking for enterprise-scale deployments

  • Use separate node pools for system and application workloads

  • Configure CSI drivers for Azure Disk and File storage

  • Leverage Azure Policy for AKS

Real-life considerations:

  • Application Gateway Ingress Controller for WAF capabilities

  • Azure Container Registry with geo-replication for multi-region deployments

  • Use Virtual Node (with Azure Container Instances) for burst workloads

GCP GKE Architecture

Best Practices:

  • Use GKE Autopilot for simplified operations

  • Enable GKE Standard clusters with node auto-provisioning

  • Implement Workload Identity for secure GCP API access

  • Configure Cloud NAT for private GKE clusters

  • Use Binary Authorization for supply chain security

Real-life considerations:

  • Multi-cluster ingress and service mesh with Cloud Service Mesh

  • GKE Enterprise for enhanced multi-cluster management

  • Container-Optimized OS for improved security posture

Multi-Cloud Kubernetes Architecture

For organizations operating across multiple clouds, these patterns enable consistent management:

Fleet Management Approach

Implementation strategies:

  • Unified configuration repository with environment-specific overlays

  • Federation layer for cross-cluster service discovery

  • Standardized CRDs across all clusters

  • Central identity management with federation to cloud IAM systems

  • Common observability and alerting platform

Network Architecture Models

Multi-Tier Network Security Model

Implementation components:

  • AWS: ALB + AWS Shield + WAF + AppMesh/Istio + Calico

  • Azure: App Gateway + Azure Firewall + Istio/Linkerd + Azure CNI + Calico

  • GCP: Cloud Load Balancer + Cloud Armor + Anthos Service Mesh + Calico

Storage Architecture Best Practices

Data-Intensive Workload Architecture

Cloud-specific recommendations:

  • AWS: Use gp3 volumes for general workloads, io2 for high-performance databases

  • Azure: Use Premium SSD v2 for dynamic scaling of performance

  • GCP: Use Regional Persistent Disks for high-availability storage

Multi-Tenancy Models

Hard Multi-tenancy

Separate clusters for each tenant ensure complete isolation.

Soft Multi-tenancy

Namespace-based isolation within a shared cluster.

Implementation tools:

  • Hierarchical namespace controller

  • Network policies with advanced CNI implementations

  • OPA Gatekeeper or Kyverno for policy enforcement

  • ResourceQuotas and LimitRanges

  • Pod Security Standards

Control Plane Scaling Considerations

API Server Scaling

Maximum number of clusters:

  • AWS EKS: 100 clusters per region per account (soft limit)

  • Azure AKS: 1000 clusters per subscription (soft limit)

  • GCP GKE: 50 clusters per project (soft limit)

Maximum nodes per cluster:

  • AWS EKS: 5,000 nodes

  • Azure AKS: 5,000 nodes

  • GCP GKE: 15,000 nodes

API server recommendations:

  • Implement efficient watch caches

  • Use server-side filtering of list requests

  • Optimize etcd for large clusters

  • Consider specialized control plane scaling for >5000 nodes

Disaster Recovery Architecture

Multi-Region Active-Passive Pattern

Recovery strategies:

  • Regular etcd snapshots with cross-region backup

  • GitOps-driven configuration ensures consistent redeployment

  • Stateful data replication with appropriate consistency models

  • DNS or global load balancer for traffic redirection

Cost Optimization Architecture

Cost-Efficient Node Design

Cloud-specific recommendations:

  • AWS: Mix Spot Instances with On-Demand and Savings Plans

  • Azure: Use Spot VMs with AKS and Azure Reservations

  • GCP: Combine Spot VMs with Committed Use Discounts

Optimization techniques:

  • Cluster autoscaler with scale-down rules

  • Pod Priority and Preemption for critical workloads

  • Right-sizing deployments with VPA

  • Implement node auto-provisioning

  • Schedule non-critical batch jobs during off-peak hours

References

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