Architecting Secure AI-Native and ML Cloud Systems on Azure

Design Patterns for Building Intelligent, Trusted, and Scalable Platforms
1. Auflage 2027
ISBN: 979-8-8688-3355-7
Verlag: APRESS L.P.

Buch, Englisch, Format (B × H): 178 mm x 254 mm

Modern cloud platforms are evolving into intelligent systems that can sense, reason, and act in real time. This book shows you how to design these next-generation platforms by embedding AI and ML directly into cloud architectures. Moving beyond traditional batch processing, the book introduces AI-native principles and the signals-to-insights-to-actions paradigm, helping you build systems that continuously learn and respond.

You’ll explore core architectural patterns, including event-driven design, scalable data and ML pipelines, and real-time inference using Azure services such as Event Grid, Azure Machine Learning, and Kubernetes Service. The book also covers MLOps, model serving, observability, and resilience—making sure your systems are production-ready and scalable.

Security and governance remain central throughout, with guidance on Zero Trust, identity-first security, responsible AI, and compliance. By the end, you’ll have a clear blueprint for architecting secure, intelligent cloud systems that deliver real-time, trusted outcomes at scale.

What You Will Learn:

• Design modern, AI-native cloud architectures on Azure that can respond in real time
• Know practical ways to integrate AI and machine learning into everyday applications
• Build secure, trustworthy systems using Zero Trust and responsible AI practices
• Discover approaches to creating scalable data pipelines and running ML models in production
• Turn continuous data signals into meaningful insights and automated actions

Who This Book Is For:

Cloud architects, developers, and AI/ML engineers who want to build secure, intelligent systems on Azure

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Singh, Harvendra

Prasad, Amit

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Computerkommunikation & -vernetzung Cloud-Computing, Grid-Computing
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Microsoft Programmierung

Inhaltsverzeichnis

Chapter 1: The Evolution to AI-Native Cloud Systems.- Chapter 2: Core Architecture Principles for AI Systems.- Chapter 3: Security by Design for AI-Native Architectures.- Chapter 4: Event-Driven Architecture for Intelligent Systems.- Chapter 5: Data Architecture for AI and Machine Learning.- Chapter 6: Machine Learning Life Cycle and MLOps.- Chapter 7: Real-Time AI and Stream Processing.- Chapter 8: AI Model Serving and Inference Architectures.- Chapter 9: Securing AI and Machine Learning Systems.- Chapter 10: Identity, Access, and Secrets Management.- Chapter 11: Observability for AI Systems.- Chapter 12: Resilience and Reliability Engineering.- Chapter 13: DevSecOps and MLOps Integration.- Chapter 14: Governance, Compliance, and Responsible AI.- Chapter 15: Future of AI-Native Cloud Architectures.

Über Autor(innen)

Harvendra Singh is a technology professional and leader specializing in cloud engineering, enterprise architecture, and AI-driven systems. He focuses on designing scalable, secure, and high-performance platforms that help organizations build modern digital solutions and make better use of data. Over the years, he has worked extensively with cloud-native technologies and distributed systems, developing applications and platforms that support large-scale digital transformation initiatives. His work centers on applying practical architectural principles to build systems that are resilient, efficient, and well suited for enterprise environments. Harvendra is passionate regarding continuous learning and knowledge sharing within the global technology community, and through technical writing, research, mentoring, and speaking engagements, he actively contributes to advancing modern cloud and AI architectures.

Amit Prasad  is a technology professional focused on designing and delivering scalable, secure, and high-performance solutions. He has contributed to numerous technology initiatives that promote innovation, improve operational efficiency, and create meaningful business value. His work spans modern cloud platforms, enterprise architecture, and emerging technologies, helping organizations build resilient and future-ready systems. Amit is passionate regarding solving complex technical challenges and fostering collaboration to deliver impactful and reliable solutions.