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OpenAI and Google Cloud AI: Build Production AI Applications with Vertex AI, Gemini, Agents, RAG, and Multi-Cloud Enterprise Automation
Paperback
Series: The Multi-Cloud OpenAI Handbook, Book 3
Publisher: Independently Published
Published: Jul 30 2026
Pages: 180
Weight: 0.95
Height: 0.38 Width: 8.50 Depth: 11.00
Language: English
Google Cloud's AI platform can do far more than power a demo. This is the hands-on, end-to-end guide to building AI applications that reach production and stay there, using Google's Gemini models, OpenAI's models, and the full power of Vertex AI and the Gemini Enterprise Agent Platform.
Most AI books stop at calling an API. This one takes you all the way: from your first model call to a secure, observable, scalable platform running real workloads. Every technique is built on the current 2026 stack, Gemini 3, the Agent Development Kit, Vertex AI Search, Agent Engine, and native MCP and A2A, including the agentic capabilities that older Google Cloud books predate entirely.
What you will build and master:
- Production chatbots with memory, streaming, and durable session state on Firestore and Cloud Run.
- Retrieval-Augmented Generation grounded in your own documents, with hybrid search, embeddings, and citations.
- Autonomous AI agents with the ADK and Agent Engine, using MCP tools, managed memory, and agent identity.
- Multi-agent systems that plan, delegate, and coordinate through open A2A protocols.
- Enterprise automation for invoices, contracts, and workflows with Document AI.
- Enterprise knowledge assistants with permission-filtered retrieval that never leaks restricted content.
- Security and governance with Cloud IAM, Secret Manager, and Model Armor guardrails.
- Observability, testing, evaluation, deployment, and cost control with Terraform and CI/CD.
- Multi-cloud architecture that runs AI across Google Cloud, AWS, and Azure without lock-in.
Who this book is for: backend and full-stack developers, cloud and platform engineers, ML engineers, solution architects, and technical leads who want to ship AI features that are reliable, secure, and built to last.
You should be comfortable with Python and basic APIs. Prior Google Cloud experience helps but is not required, the book builds your foundation from a new project, with a companion code repository organized by chapter and production checklists in every chapter.
What sets this book apart: it teaches the current agentic Google Cloud stack, not the deprecated approach found in older titles, and it is the only guide that shows you how to run the same production AI across all three major clouds.
Twenty focused chapters across five parts, plus twelve reference appendices, take you from foundations to a complete multi-cloud production AI platform.
Stop building demos. Start shipping production AI. Scroll up and grab your copy today.
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