Managed Kubernetes platforms provide enterprises with production-ready Kubernetes clusters where cloud providers handle control plane operations, upgrades, availability, and infrastructure scaling—allowing teams to focus on application deployment rather than cluster administration. The three dominant platforms—Amazon EKS, Azure AKS, and Google GKE—offer distinct approaches to networking, identity management, autoscaling, and cost models, with GKE pioneering Kubernetes features first, EKS integrating deeply with AWS services, and AKS offering free control plane management. Understanding node group strategies, CNI plugin choices, storage driver configurations, and platform-specific authentication mechanisms becomes critical when architecting multi-cluster, multi-region production environments that require predictable availability, security compliance, and cost optimization at scale.
What This Cheat Sheet Covers
This topic spans 16 focused tables and 132 indexed concepts. Below is a complete table-by-table outline of this topic, spanning foundational concepts through advanced details.
Table 1: Platform Comparison - Core Service Features
| Platform | Example | Description |
|---|---|---|
Control plane $0.10/hour No free tier | • AWS-managed Kubernetes with tight integration to IAM, VPC, EBS • pay for control plane + worker nodes • Pod Identity simplifies AWS service access • supports Fargate serverless and managed node groups. | |
Free control plane Pay only for nodes | • Azure's managed Kubernetes with free control plane (no per-hour charge) • integrates Azure AD, managed identities, ACR • supports virtual nodes (ACI), KEDA event-driven scaling, and workload identity federation. | |
Standard mode: $0.10/hour Autopilot: pod-based pricing | • Most mature managed Kubernetes (Google invented K8s) • offers Standard mode (full node control) and Autopilot mode (fully managed, no nodes) • Workload Identity native integration • fastest feature rollouts • container-native load balancing. | |
Pay per pod resource usage $0.0445/vCPU-hour (2026) | • Fully managed serverless Kubernetes where you define only pods—no node management • Google handles scaling, security hardening, updates • charges based on actual pod resource requests (vCPU, memory, ephemeral storage). | |
Control plane + compute costs Full node customization | • Traditional managed Kubernetes with full control over node configuration, OS, GPUs, local SSDs • you manage scaling, security policies, node pools • ideal for custom workloads, Windows nodes, hybrid deployments. |