Scalable Artificial Intelligence Systems Cloud Native Edge Ai Mlops And Governance For Real World Deployment
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Scalable Artificial Intelligence Systems: Cloud-Native, Edge-AI, MLOps, and Governance for Real-World Deployment
Author: Swarup Panda
language: en
Publisher: Deep Science Publishing
Release Date: 2025-07-28
Artificial Intelligence (AI) has become essential across industries, transforming operations, decision-making, and value creation. As organizations worldwide use AI to address challenges in areas like healthcare, finance, cybersecurity, manufacturing, and infrastructure, the need for reliable and scalable AI systems continues to grow. This book offers practical guidance for professionals designing and deploying scalable, compliant AI solutions in production environments. It covers modernizing legacy systems, building MLOps pipelines, and addressing ethical aspects of autonomous AI, providing essential insights and patterns for real-world applications. We cover essential topics for enterprise AI success, such as scalable architectures (cloud-native, edge, hybrid), MLOps for lifecycle management, and governance for compliance and fairness. The text also outlines frameworks for explainable and federated AI in regulated fields, supporting privacy and distributed intelligence. We demonstrate AI's impact on diagnostics, fraud detection, threat intelligence, and urban planning through case studies, and review how platforms like Azure, AWS, and GCP support scalable AI deployment. This book highlights the need for ethical AI that upholds human values, privacy, and transparency. As AI shapes society, we must design, deploy, and govern it responsibly. I invite you to explore these chapters with a mindset of both innovation and accountability—as together, we shape a future powered by intelligent and responsible systems.
Cloud Native Infrastructure
Author: Justin Garrison
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2017-10-25
Cloud native infrastructure is more than servers, network, and storage in the cloud—it is as much about operational hygiene as it is about elasticity and scalability. In this book, you’ll learn practices, patterns, and requirements for creating infrastructure that meets your needs, capable of managing the full life cycle of cloud native applications. Justin Garrison and Kris Nova reveal hard-earned lessons on architecting infrastructure from companies such as Google, Amazon, and Netflix. They draw inspiration from projects adopted by the Cloud Native Computing Foundation (CNCF), and provide examples of patterns seen in existing tools such as Kubernetes. With this book, you will: Understand why cloud native infrastructure is necessary to effectively run cloud native applications Use guidelines to decide when—and if—your business should adopt cloud native practices Learn patterns for deploying and managing infrastructure and applications Design tests to prove that your infrastructure works as intended, even in a variety of edge cases Learn how to secure infrastructure with policy as code
Microsoft Azure Essentials Azure Machine Learning
Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.