Vertex AI in Production: End-to-End ML and Generative AI Deployment on Google Cloud

By Rodrigo Menezes

Build, deploy, scale, and manage production-ready machine learning and generative AI systems using Google Cloud Vertex AI.

Artificial intelligence is rapidly moving from experimentation to production. Organizations today need more than isolated machine learning models-they need scalable AI platforms capable of training, deploying, monitoring, securing, and operationalizing AI systems across real-world enterprise environments.

Google Cloud Vertex AI has emerged as one of the most powerful unified AI platforms for building modern machine learning and generative AI applications at scale.

Vertex AI in Production is a practical, end-to-end guide for developers, machine learning engineers, MLOps professionals, cloud architects, data scientists, and enterprise AI teams who want to move beyond prototypes and build production-grade AI systems on Google Cloud.

What You'll Learn
Master Google Cloud Vertex AI

Learn how to use Vertex AI for:

Machine learning model developmentGenerative AI application deploymentMLOps automationAI workflow orchestrationReal-time and batch inferenceModel monitoring and governance

Understand how Vertex AI simplifies the full machine learning lifecycle from experimentation to production deployment.

Build End-to-End ML Pipelines

Learn how to:

Prepare and manage datasetsTrain machine learning modelsAutomate feature engineeringDeploy scalable prediction endpointsBuild reproducible ML workflowsImplement CI/CD for machine learning

Includes practical examples using real-world enterprise deployment patterns.

Deploy Generative AI Applications

Explore modern generative AI development using:

Gemini modelsPrompt engineeringRetrieval-Augmented Generation (RAG)Vector searchAI agents and orchestrationEnterprise AI assistants

Learn how to build secure and scalable AI-powered applications using Vertex AI and Google Cloud infrastructure.

Production MLOps & AI Infrastructure

Master enterprise-grade AI operations including:

Vertex AI PipelinesModel RegistryExperiment trackingAutomated training workflowsKubernetes and containerized deploymentInfrastructure scaling and optimization

Understand how leading organizations operationalize AI systems reliably at scale.

Monitoring, Security & Governance

Learn best practices for:

Model monitoring and drift detectionAI observabilityResponsible AI implementationData governance and complianceIAM and security architectureCost optimization and performance tuning

Perfect for organizations deploying AI in regulated and high-scale environments.

Real-World AI Projects

Build practical production systems including:

Generative AI chat applicationsRecommendation enginesIntelligent document processing systemsPredictive analytics platformsEnterprise AI search systemsReal-time ML inference pipelines

Each chapter focuses on practical implementation strategies and production-oriented architecture guidance.

Build Production-Ready AI on Google Cloud

From machine learning pipelines and generative AI deployment to MLOps automation and enterprise AI governance, this is your complete guide to mastering Vertex AI in production.

• Format: Paperback
• Language: English
• ISBN: B0H25KC5XZ
• ISBN13: 9798197349736
• Release Date: May 2026
• Publisher: Independently Published
• Length: 178 Pages
• Weight: 0.94 lbs.
• Dimensions: 0.4" x 8.5" x 11.0"