A developer spins up clusters on GKE while another tweaks a CloudFormation stack. One cloud uses YAML comfort food, the other eats YAML for breakfast but speaks in a different accent. You could keep documenting brittle scripts, or you could make these tools actually cooperate.
CloudFormation defines AWS infrastructure with predictable templates. Google Kubernetes Engine orchestrates containers reliably at scale. Combining them lets operations teams manage multi-cloud systems with shared intent and version control. When done right, CloudFormation Google Kubernetes Engine builds feel like one continuous environment instead of rival planets.
CloudFormation can’t directly spin up GKE clusters because it’s AWS-native, but you can bridge them using custom resources and service identities. The pattern is simple: use CloudFormation to define your logic and trigger a deployment agent that configures your GKE cluster via authenticated API calls. Identity and access are handled through IAM roles or OIDC providers, so each environment stays isolated yet under a single governance model.
This setup turns fragmented automation into a coherent workflow. One pipeline provisions IAM roles in AWS, another authorizes those roles to hit GCP endpoints, and a webhook handles the Kubernetes configuration inside the target cluster. The trick is managing credentials once, in one place, without hardcoding secrets or juggling service accounts across systems.
Best Practice: Cross-Cloud Identity via OIDC
If you must pass identity tokens between AWS and GCP, use OIDC federation. It binds access decisions to verified identity rather than stored keys. Map those roles to Kubernetes RBAC groups so developers see consistent permissions everywhere. It’s cleaner, and it kills off “temporary admin” emergencies before they start.