About This Architecture

AI Gateway Architecture on Google Cloud routes requests from multiple client types—Claude Code, Codex, IDE Assistants, and custom agents—through a Global HTTPS Load Balancer to three specialized Cloud Run services: Dashboard, LLM Gateway, and Control-Plane. The LLM Gateway abstracts access to diverse model providers including Vertex AI, Amazon Bedrock, Azure AI Foundry, StackIT, and Evroc, with secrets managed by Secret Manager and task orchestration via Cloud Tasks and Scheduler. Cloud SQL stores application state, while Cloud Logging and Cloud Monitoring provide audit trails and observability across the entire multi-cloud LLM ecosystem. This architecture decouples client applications from underlying model provider APIs, enabling seamless switching between LLM vendors and centralized governance. Fork this diagram on Diagrams.so to customize regions, add additional model providers, or adapt the control-plane logic for your organization's AI governance requirements.

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How do I build a multi-cloud LLM gateway on Google Cloud that routes requests to Vertex AI, Amazon Bedrock, and Azure AI?

This diagram shows a Google Cloud AI Gateway using Cloud Run services (Dashboard, LLM Gateway, Control-Plane) behind a Global HTTPS Load Balancer to abstract and route LLM requests to multiple providers. The LLM Gateway manages secrets via Secret Manager, orchestrates tasks with Cloud Tasks and Scheduler, and logs all activity through Cloud Logging and Cloud Monitoring for compliance and observabi

AI Gateway Architecture on Google Cloud

MultiadvancedGoogle Cloudmulti-cloudLLM gatewayCloud RunAI architectureVertex AI
Domain: Cloud MultiAudience: Cloud architects designing multi-cloud LLM gateway infrastructure on Google Cloud
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Created by

July 22, 2026

Updated

August 3, 2026 at 10:59 AM

Type

architecture

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