Amazon EKS Google GKE vs similar tools: which fits your stack best?

Your cluster crashed at 2 a.m. again, and now the debate begins: do we standardize on Amazon EKS or Google GKE? Both promise managed Kubernetes without the on-call nightmares. Both hide control plane pain. Yet, the moment you mix multi-cloud or identity policies, their stories diverge.

Amazon EKS keeps you deep in AWS territory. It syncs perfectly with IAM, CloudWatch, and VPC-level isolation. Google GKE leans on simplicity, faster autoscaling, and baked‑in insights from GCP’s telemetry stack. If you squint, they’re twins raised in different households. What’s surprising is how often teams need both.

A growing number of enterprises run workloads across EKS and GKE to avoid lock‑in, chase regional pricing, or use specialized AI hardware. Their Kubernetes manifests look similar, but behind the scenes, credentials, access tokens, and network rules create a maze. The trick is to line up identity once, then let each cluster trust that same source.

Here’s the flow that works: centralize identity with OIDC or an SSO provider like Okta. Map roles through short‑lived tokens using AWS IAM roles for service accounts on EKS and Workload Identity on GKE. Then automate context: which developer, which namespace, which service. Once identity is portable, everything downstream moves faster and fails less.

Typical pain points start with RBAC drift. A role created in one cloud rarely matches its twin in another. Avoid static YAML copies and automate policy sync instead. Next, manage secret rotation through external secrets managers so API keys never linger. Finally, watch your audit trails; a cross‑cloud setup only works if your logs agree on who did what and when.

You get clear benefits from unifying Amazon EKS and Google GKE:

• Consistent access control across providers.
• Reduced multi-cloud drift and misconfigurations.
• Faster onboarding for developers moving between projects.
• Single audit flow for compliance frameworks like SOC 2 or ISO 27001.
• Better cost awareness by aligning clusters under one operational lens.

For developers, this integration cuts context-switching. You write once, deploy anywhere, and stop hunting for IAM roles that changed overnight. Less yak shaving, more shipping. It also opens doors to automation. AI copilots can suggest optimal node scaling or surface RBAC anomalies directly in pull requests because they read a unified identity graph rather than two clouds with different names for “team-admin.”

Platforms like hoop.dev make this model practical. They translate identity and access policies into live guardrails that enforce permissions across both Amazon EKS and Google GKE. Teams stop wiring manual gateways and start trusting that their proxy already enforces least privilege.

How do I connect Amazon EKS and Google GKE clusters for shared identity?
Use a common OIDC identity provider tied to both clouds. Each cluster trusts that provider to issue short-lived tokens, allowing secure cross‑cloud access without static credentials.

Can I use one CI/CD pipeline for EKS and GKE?
Yes. As long as your pipeline injects credentials dynamically per environment, you can push images and configs to both without hardcoded secrets.

The short answer: Amazon EKS and Google GKE each shine, but their real power appears when you connect them under one identity and policy umbrella. That is where platform engineering stops patching and starts designing.

See an Environment Agnostic Identity-Aware Proxy in action with hoop.dev. Deploy it, connect your identity provider, and watch it protect your endpoints everywhere—live in minutes.