Designing Scalable and Intelligent Cloud Architectures: An End-to-End Guide to AI Driven Platforms, MLOps Pipelines, and Data Engineering for Digital Transformation
##plugins.pubIds.doi.readerDisplayName##
https://doi.org/10.70593/978-93-49910-08-9
Keywords:
Cloud Computing, Artificial Intelligence, Machine Learning, MLOps, Cloud-Native Architecture, Microservices, Big Data AnalyticsSynopsis
In today’s fast-paced digital era, organizations are under constant pressure to innovate, scale, and deliver intelligent services with speed and reliability. Designing Scalable and Intelligent Cloud Architectures: An End-to-End Guide to AI-Driven Platforms, MLOps Pipelines, and Data Engineering for Digital Transformation is a comprehensive exploration into the foundational and advanced components required to build robust, future-ready cloud ecosystems. This book is the product of years of observing the shifting paradigms in enterprise IT—from legacy systems and monolithic architectures to microservices, serverless computing, and AI-powered infrastructure. At the heart of this evolution lies the need for cloud-native platforms that are not only scalable and resilient but also intelligent and automation-ready.
The content in these pages is aimed at architects, engineers, data scientists, DevOps professionals, and digital transformation leaders who seek to understand and implement the key building blocks of modern cloud systems. It delves into the design principles behind scalable infrastructure, best practices for integrating AI and Machine Learning, and the implementation of MLOps pipelines to streamline deployment, monitoring, and continuous improvement of ML models. Furthermore, it provides practical insights into data engineering strategies that ensure secure, efficient, and real-time data flow across distributed environments. We also explore critical topics such as multi-cloud and hybrid cloud strategies, edge computing, observability, cost optimization, and governance—ensuring that readers are equipped to tackle both the technical and operational challenges of building next-generation platforms.
What sets this book apart is its unified approach to cloud, AI, and data engineering—treating them not as isolated silos but as interconnected pillars of intelligent digital transformation. Whether you are designing enterprise-grade solutions or modernizing existing infrastructures, this guide will serve as your companion in navigating complexity with clarity and confidence.
Chapters
-
Building foundations for intelligent cloud infrastructure with a focus on scalability and security
-
Integrating artificial intelligence into cloud platforms for next-generation business intelligence solutions
-
Designing and deploying scalable MLOps pipelines for continuous artificial intelligence model training and delivery
-
Best practices in building secure, compliant, and resilient cloud-native architectures for artificial intelligence workloads
-
Infrastructure as code and automation tools for efficient multi-cloud resource provisioning
-
Architecting advanced data pipelines using real-time streaming and batch processing technologies
-
Strategies for high availability, disaster recovery, and performance in multi-cloud deployments
-
Applying data engineering principles to build distributed, scalable, and fault-tolerant data systems
-
Performance monitoring and optimization of machine learning models in production environments
-
Automating decision-making and operational workflows with artificial intelligence-powered cloud services
-
Leveraging cloud-native microservices, containers, and serverless architectures for artificial intelligence pipelines
-
Exploring the future of cloud computing: Autonomous systems, edge artificial intelligence, and intelligent workload management
Downloads
Published
6 June 2025
Copyright (c) 2025 Phanish Lakkarasu
Details about the available publication format: E-Book
E-Book
ISBN-13 (15)
978-93-49910-08-9
Details about the available publication format: Book (Paperback)
Book (Paperback)
ISBN-13 (15)
978-93-49910-01-0
How to Cite
Lakkarasu, P. . (2025). Designing Scalable and Intelligent Cloud Architectures: An End-to-End Guide to AI Driven Platforms, MLOps Pipelines, and Data Engineering for Digital Transformation. Deep Science Publishing. https://doi.org/10.70593/978-93-49910-08-9
Download Citation
