Independent comparison for enterprise buyers. Updated May 2026.
Quick verdict: Choose Amazon EKS for organisations standardised on AWS where deep IAM, VPC, and other AWS service integrations are decisive. Choose Google GKE for organisations that want the most mature managed Kubernetes from the team that created Kubernetes, with Autopilot reducing operational overhead. The key differentiator is operational philosophy: EKS leaves more control with the customer, GKE Autopilot pushes more responsibility to Google.
| Criteria | Amazon EKS | Google GKE |
|---|---|---|
| Editorial score | 4.4 / 5.0 | 4.5 / 5.0 |
| Deployment | EKS, EKS Anywhere, EKS Hybrid Nodes | GKE Standard, GKE Autopilot, GKE Enterprise (multi-cloud) |
| Pricing Model | $0.10 per cluster per hour plus node compute | $0.10 per cluster per hour plus node compute, free first cluster |
| Target Buyer | AWS-aligned enterprises, broad workload portability | Data and ML workloads, Google Cloud-aligned enterprises |
| Implementation | 4–12 weeks typical for production | 2–8 weeks typical, faster with Autopilot |
| Customisation | Customer-managed node pools, add-ons, IRSA | Workload Identity, Autopilot constraints, Anthos Config Management |
| Ecosystem | AWS service integration, marketplace add-ons | Google Cloud integration, Anthos ecosystem |
| Key Strength | AWS-native integration, broadest cloud footprint | Kubernetes maturity, Autopilot operational simplicity |
Amazon EKS provides managed control plane for Kubernetes on AWS with deep integration into AWS services. EKS integrates natively with IAM through IAM Roles for Service Accounts (IRSA) and Pod Identity, with VPC through the AWS VPC CNI plugin, with EBS and EFS for persistent storage, with ALB and NLB for load balancing, and with CloudWatch and AWS X-Ray for observability. EKS Anywhere extends Kubernetes to on-premise environments, and EKS Hybrid Nodes allow on-premise compute to join EKS clusters managed in AWS.
Google GKE is widely regarded as the most operationally mature managed Kubernetes platform, reflecting Google's role as the primary creator of Kubernetes. GKE Standard provides traditional managed Kubernetes with customer-managed node pools, while GKE Autopilot abstracts node management entirely, with Google operating the underlying compute and customers paying per pod resource consumption. GKE integrates natively with Google Cloud Workload Identity, Cloud Logging, Cloud Monitoring, and BigQuery, and supports advanced workloads such as Anthos Service Mesh and TPU-attached pods for ML training and inference.
For multi-cluster and hybrid scenarios, GKE Enterprise (formerly Anthos) extends consistent Kubernetes management across Google Cloud, AWS, Azure, and on-premise via Anthos clusters. EKS offers comparable extension through EKS Anywhere, although the multi-cloud reach is narrower than GKE Enterprise. For data-intensive and ML workloads, GKE has consistently led in supporting GPU autoscaling, TPU integration, and Kueue-based batch scheduling.
On Kubernetes version support and patching, GKE tends to support new Kubernetes versions slightly ahead of EKS and applies control plane patches automatically with configurable release channels. EKS has narrowed this gap with extended support periods for Kubernetes versions, which appeals to enterprises that prefer slower upgrade cycles. Both platforms are CNCF-conformant and run unmodified upstream Kubernetes.
Amazon EKS charges $0.10 per cluster per hour for the managed control plane, plus underlying EC2 or Fargate compute costs. Extended support for older Kubernetes versions costs an additional $0.50 per cluster per hour. As of May 2026 a typical EKS production cluster runs in the range of $5K–$50K per month depending on node count, instance type, and reserved capacity commitments. Buyers should plan for data transfer charges across availability zones and for NAT gateway costs, both of which can grow materially in chatty microservice architectures.
Google GKE also charges $0.10 per cluster per hour for clusters beyond the first free zonal cluster, with GKE Autopilot pricing based on requested pod CPU, memory, and ephemeral storage rather than node compute. As of May 2026 GKE Autopilot typically prices 10–20% higher than equivalent GKE Standard for steady workloads, but reduces operational overhead and node-level waste. The hidden cost trap on EKS is data egress and NAT gateway charges; the hidden cost trap on GKE Autopilot is pod resource over-provisioning that bills regardless of actual utilisation.
Choose Amazon EKS if your organisation is standardised on AWS with material existing IAM, VPC, and service integrations, if you operate workloads requiring deep AWS-native services such as S3, DynamoDB, Aurora, or SageMaker, or if your workload portfolio benefits from EKS's broader AWS region footprint and reserved capacity options. EKS is also the pragmatic default for organisations with existing AWS spend commitments where consolidating Kubernetes on AWS strengthens negotiating position with AWS.
Choose Google GKE if you want the most operationally mature managed Kubernetes platform, if your workloads include significant data analytics or ML training where BigQuery, Vertex AI, and TPU integration are valuable, or if Autopilot's operational model matches your team's preference for reduced node management overhead. GKE is also a strong fit for organisations adopting multi-cloud Kubernetes through GKE Enterprise, and for engineering-led companies where Google Cloud's developer experience aligns with operational preference.
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