The Real Cost of Choosing Between EKS and GKE

The decision between Amazon Elastic Kubernetes Service and Google Kubernetes Engine rarely hinges on the Kubernetes API, which is identical across both platforms. It comes down to the infrastructure surrounding that API: networking defaults, identity integration, autoscaling mechanisms, and the specific financial structure of the control plane. For teams already entrenched in AWS or GCP, the choice is often predetermined by ecosystem dependencies rather than technical superiority. However, for those starting fresh or considering a migration, the operational trade-offs are significant enough to warrant a detailed cost-benefit analysis before committing to a cloud provider.

Control Plane Economics and Node Management

EKS charges $0.10 per hour for each cluster, which amounts to roughly $73 per month per cluster. This fee applies regardless of cluster size or usage, making it a fixed overhead that accumulates quickly if you run multiple environments like development, staging, and production. GKE, by contrast, offers a free control plane for its Standard and Autopilot modes, eliminating this baseline expense entirely. At scale, five separate clusters on EKS incur over $4,400 in annual control plane fees alone, while the same setup on GKE costs nothing for the control plane itself. This difference is not trivial for organizations managing dozens of clusters, as the savings can be redirected toward compute resources or storage.

Node management further differentiates the two services. EKS relies on Karpenter for intelligent node provisioning, a tool that originated on AWS and provides deep integration with instance selection and bin-packing. Karpenter allows for aggressive consolidation and supports mixed spot and on-demand nodes within the same pool, offering granular control over resource efficiency. GKE Autopilot takes a different approach by removing node management from the equation entirely; users declare pods, and Google provisions and manages the underlying nodes automatically. While this reduces operational burden, it limits flexibility compared to Karpenter’s precise control. GKE Standard mode uses the built-in cluster autoscaler, which is mature but less flexible than Karpenter. Teams that prioritize zero node operations may find Autopilot appealing, but those requiring specific instance types or complex scheduling logic will likely prefer EKS with Karpenter.

Networking, Identity, and Ecosystem Integration

Networking architecture often dictates the final decision more than any other factor. EKS uses the AWS VPC CNI by default, assigning each pod a real VPC IP address. This allows native security groups and routing at the pod level but introduces the risk of IP address exhaustion in large clusters. GKE uses VPC-native networking with alias IP ranges, which manages IP space more efficiently and reduces exhaustion concerns. GKE also includes Cilium as the default network policy engine, providing built-in support for advanced networking features without additional add-ons. EKS requires installing Calico or another CNI for equivalent network policy enforcement, adding complexity to the initial setup.

Identity integration follows similar patterns tied to the parent cloud provider. EKS uses IAM Roles for Service Accounts or EKS Pod Identity, allowing pods to assume IAM roles without static credentials. This integrates seamlessly with AWS SSO and other OIDC providers. GKE uses Workload Identity Federation, where pods impersonate Google Cloud service accounts, tying directly into Google Cloud IAM and Workspace. If your organization manages users in Azure AD or AWS IAM, the corresponding service offers frictionless identity handling. Switching clouds solely for Kubernetes features usually incurs higher migration costs in IAM, networking, and CI/CD pipelines than the operational savings gained from a better autoscaler or free control plane.

GKE tends to have new Kubernetes versions available first among major providers, supporting each version for approximately 14 months on the Regular channel. EKS also supports versions for about 14 months but charges an extended support fee of $0.60 per hour per cluster for older versions. This extended support cost can become expensive for teams unable to upgrade frequently due to compliance or legacy dependencies. The ecosystem breadth also differs; EKS has the largest third-party tooling market, with every CNCF tool and observability vendor offering first-class support. GKE is more batteries-included, with managed add-ons for Config Sync, Anthos Service Mesh, and Binary Authorization reducing the need for external tools. Which path suits your team depends on whether you prefer assembling a best-of-breed stack or accepting a curated, first-party experience.