Google Cloud
Run agentgateway on GCP to leverage Vertex AI, GKE, and Google Cloud services.
Deployment options
Google Kubernetes Engine (GKE)
For GKE deployments, use Agentgateway on Kubernetes which provides native Kubernetes Gateway API support, dynamic configuration, and MCP service discovery.
Cloud Run
Run agentgateway as a serverless container on Cloud Run.
gcloud run deploy agentgateway \
--image ghcr.io/agentgateway/agentgateway:latest \
--port 3000 \
--set-env-vars "GOOGLE_CLOUD_PROJECT=my-project" \
--service-account agentgateway@my-project.iam.gserviceaccount.com \
--allow-unauthenticatedGCP integrations
| Integration | Purpose |
|---|---|
| Vertex AI | Access Gemini and other models |
| Google Gemini | Direct Gemini API access |
| GCP Secret Manager | Secure API key storage |
| Cloud Load Balancing | Global load balancing with SSL |
| Cloud Trace | Distributed tracing |
| Cloud Monitoring | Metrics and alerting |
IAM permissions
Create a service account with these roles:
# Create service account
gcloud iam service-accounts create agentgateway \
--display-name "agentgateway"
# Grant Vertex AI access
gcloud projects add-iam-policy-binding my-project \
--member "serviceAccount:agentgateway@my-project.iam.gserviceaccount.com" \
--role "roles/aiplatform.user"
# Grant Secret Manager access
gcloud projects add-iam-policy-binding my-project \
--member "serviceAccount:agentgateway@my-project.iam.gserviceaccount.com" \
--role "roles/secretmanager.secretAccessor"