{"product_id":"ai-native-cloud-engineering-designing-deploying-and-governing-scalable-machine-learning-systems-for-architects-cloud-engineers-and-mlops-professi-9798250091725","title":"Ai-Native Cloud Engineering: Designing, Deploying, and Governing Scalable Machine Learning Systems for Architects, Cloud Engineers, and MLOps Professi","description":"\u003cp\u003e • Author(s): Ronald Laffey\u003cbr\u003e • Publisher: Independently Published\u003cbr\u003e • Publisher Imprint: Independently Published\u003cbr\u003e • BISAC: Artificial Intelligence - Generative AI\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAI is no longer an experiment, it is infrastructure. The question is: are you architecting for it correctly?\u003c\/p\u003e\u003cp\u003eAI-Native Cloud Engineering is a practical, enterprise-grade guide for architects, cloud engineers, and MLOps professionals who are ready to move beyond basic model deployment and design truly scalable, governed, and autonomous AI systems. This book bridges the gap between machine learning theory and production-ready cloud architecture, showing you how to build intelligent systems that are resilient, cost-efficient, compliant, and future-ready.\u003c\/p\u003e\u003cp\u003eInside, you will learn how to design distributed GPU architectures for large-scale training and inference, implement feature stores and vector databases, operationalize Retrieval-Augmented Generation (RAG), and build CI\/CD pipelines tailored specifically for machine learning workflows. You will master AI observability, drift detection, hallucination monitoring, zero-trust AI security, and FinOps strategies that prevent runaway cloud costs. Most importantly, you will understand how to embed autonomy into your systems through agentic workflows, predictive autoscaling, and self-healing infrastructure.\u003c\/p\u003e\u003cp\u003eThis book does not stay at the surface. It goes deep into production realities, governance frameworks, compliance alignment, hybrid and multi-cloud orchestration, green AI practices, and the operational lessons learned from large-scale deployments across fintech, healthcare, and e-commerce. Every chapter is designed to connect architecture decisions directly to business impact.\u003c\/p\u003e\u003cp\u003eThe unique strength of this book lies in its AI-native perspective. Instead of treating AI as an add-on service running on traditional cloud systems, it teaches you how to design cloud environments where intelligence is foundational, where infrastructure learns, scales, and optimizes itself. You are not just deploying models; you are engineering intelligent ecosystems.\u003c\/p\u003e\u003cp\u003eIf you are building enterprise AI systems, transitioning into AI-first architecture, or leading cloud modernization initiatives, this book will give you the frameworks, patterns, and strategic clarity to operate with confidence at scale.\u003c\/p\u003e\u003cp\u003eThe future belongs to AI-first enterprises. Equip yourself with the architecture mindset to lead them.\u003c\/p\u003e\u003cp\u003eGet your copy of AI-Native Cloud Engineering today and start building systems that don't just run AI, but are built for it.\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":47568807231639,"sku":"9798250091725","price":2010.0,"currency_code":"INR","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0666\/3471\/1191\/files\/9798250091725.webp?v=1774870967","url":"https:\/\/atlanticbooks.com\/products\/ai-native-cloud-engineering-designing-deploying-and-governing-scalable-machine-learning-systems-for-architects-cloud-engineers-and-mlops-professi-9798250091725","provider":"Atlantic Books","version":"1.0","type":"link"}