Architecting Intelligent Cloud Systems Ai Mlops And Scalable Infrastructure For The Future
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Architecting Intelligent Cloud Systems Ai Mlops And Scalable Infrastructure For The Future
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Author : PHANISH LAKKARASU
language : en
Publisher: Global Pen Press UK PUBLICATION
Release Date :
Architecting Intelligent Cloud Systems Ai Mlops And Scalable Infrastructure For The Future written by PHANISH LAKKARASU and has been published by Global Pen Press UK PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Architecture categories.
Designing Scalable And Intelligent Cloud Architectures An End To End Guide To Ai Driven Platforms Mlops Pipelines And Data Engineering For Digital Transformation
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Author : Phanish Lakkarasu
language : en
Publisher: Deep Science Publishing
Release Date : 2025-06-06
Designing Scalable And Intelligent Cloud Architectures An End To End Guide To Ai Driven Platforms Mlops Pipelines And Data Engineering For Digital Transformation written by Phanish Lakkarasu and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
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.
Architecting The Future Of Data Oracle Sharding Cloud Intelligence And Scalable Enterprise Systems 2025
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Author : Author:1- Sarvesh Kumar Gupta, Author:2-Dr. Lalit Kumar
language : en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date :
Architecting The Future Of Data Oracle Sharding Cloud Intelligence And Scalable Enterprise Systems 2025 written by Author:1- Sarvesh Kumar Gupta, Author:2-Dr. Lalit Kumar and has been published by RAVEENA PRAKASHAN OPC PVT LTD this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE In the digital age, data has become the driving force behind business decision-making, customer experiences, and technological innovation. As organizations strive to harness the full potential of their data, the need for scalable, efficient, and resilient data architectures has never been greater. Traditional monolithic database systems are often insufficient to handle the massive volumes, variety, and velocity of data generated by modern enterprises. Enter Oracle Sharding, Cloud Intelligence, and scalable enterprise systems—the cornerstone technologies that enable organizations to meet the demands of the data-driven future.Architecting the Future of Data: Oracle Sharding, Cloud Intelligence, and Scalable Enterprise Systems offers a comprehensive exploration of how these cutting-edge technologies are reshaping the landscape of enterprise data management. This book provides in-depth insights into how organizations can design and implement scalable, cloud-native database architectures that allow for seamless data distribution, faster processing, and enhanced performance. By focusing on Oracle Sharding, cloud intelligence, and enterprise scalability, this book aims to equip IT professionals, data architects, and business leaders with the knowledge and tools required to build the next generation of enterprise systems. The foundation of this book is Oracle’s Sharding technology, which offers an innovative approach to database architecture by horizontally partitioning data across multiple databases, or shards. This approach enhances both performance and scalability, allowing organizations to process vast amounts of data across distributed environments while ensuring high availability, fault tolerance, and efficient resource utilization. As businesses increasingly adopt cloud platforms, Oracle Sharding proves to be a critical tool for managing data in distributed cloud environments, ensuring seamless data access and faster query performance even as data volumes grow exponentially. Furthermore, cloud intelligence plays a pivotal role in enabling organizations to build smarter, more adaptive systems. As cloud technologies evolve, leveraging intelligent data processing, machine learning (ML), and artificial intelligence (AI) has become a game-changer for businesses looking to extract deeper insights from their data and improve operational efficiencies. This book delves into how cloud intelligence, when integrated with scalable data architectures like Oracle Sharding, allows enterprises to process, analyze, and gain real-time insights from massive datasets. The ability to deploy AI models directly within the cloud infrastructure enhances predictive capabilities, automates decision-making processes, and drives innovation. Scalable enterprise systems are essential for organizations to maintain their competitive edge in a rapidly changing business environment. As companies expand their digital footprints and create more data-intensive applications, the need for scalable, distributed data architectures has become crucial. This book explores the design principles and best practices for creating cloud-native enterprise systems that can adapt to growing data demands while ensuring high performance and security. By understanding the synergy between Oracle Sharding and cloud intelligence, organizations can build resilient systems capable of handling the complexities of modern data workflows. Throughout the chapters, we will cover not only the technical aspects of these technologies but also real-world use cases and best practices from leading companies who have successfully adopted Oracle Sharding and cloud-based data architectures. This book aims to bridge the gap between theoretical concepts and practical implementation, offering readers actionable strategies for building scalable, cloud-native data systems that align with business goals and technological advancements. As organizations continue to embrace digital transformation and the cloud becomes the backbone of modern IT infrastructure, understanding how to design and implement scalable, intelligent data architectures is more critical than ever. Whether you are an IT architect, database administrator, or business leader, Architecting the Future of Data will provide you with the insights and strategies necessary to navigate the challenges and opportunities of modern data management. The future of data is distributed, intelligent, and scalable—this book will guide you in shaping that future within your organization. Authors
Building Cloud Native Ai And Mlops Platforms For Scalable Secure And Mission Critical Intelligence Systems
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Author : Phanish Lakkarasu
language : en
Publisher: AQUA PUBLICATIONS
Release Date :
Building Cloud Native Ai And Mlops Platforms For Scalable Secure And Mission Critical Intelligence Systems written by Phanish Lakkarasu and has been published by AQUA PUBLICATIONS this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
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Architecting Google Cloud Solutions
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Author : Victor Dantas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-05-14
Architecting Google Cloud Solutions written by Victor Dantas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-14 with Computers categories.
Achieve your business goals and build highly available, scalable, and secure cloud infrastructure by designing robust and cost-effective solutions as a Google Cloud Architect. Key FeaturesGain hands-on experience in designing and managing high-performance cloud solutionsLeverage Google Cloud Platform to optimize technical and business processes using cutting-edge technologies and servicesUse Google Cloud Big Data, AI, and ML services to design scalable and intelligent data solutionsBook Description Google has been one of the top players in the public cloud domain thanks to its agility and performance capabilities. This book will help you design, develop, and manage robust, secure, and dynamic solutions to successfully meet your business needs. You'll learn how to plan and design network, compute, storage, and big data systems that incorporate security and compliance from the ground up. The chapters will cover simple to complex use cases for devising solutions to business problems, before focusing on how to leverage Google Cloud's Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) capabilities for designing modern no-operations platforms. Throughout this book, you'll discover how to design for scalability, resiliency, and high availability. Later, you'll find out how to use Google Cloud to design modern applications using microservices architecture, automation, and Infrastructure-as-Code (IaC) practices. The concluding chapters then demonstrate how to apply machine learning and artificial intelligence (AI) to derive insights from your data. Finally, you will discover best practices for operating and monitoring your cloud solutions, as well as performing troubleshooting and quality assurance. By the end of this Google Cloud book, you'll be able to design robust enterprise-grade solutions using Google Cloud Platform. What you will learnGet to grips with compute, storage, networking, data analytics, and pricingDiscover delivery models such as IaaS, PaaS, and SaaSExplore the underlying technologies and economics of cloud computingDesign for scalability, business continuity, observability, and resiliencySecure Google Cloud solutions and ensure complianceUnderstand operational best practices and learn how to architect a monitoring solutionGain insights into modern application design with Google CloudLeverage big data, machine learning, and AI with Google CloudWho this book is for This book is for cloud architects who are responsible for designing and managing cloud solutions with GCP. You'll also find the book useful if you're a system engineer or enterprise architect looking to learn how to design solutions with Google Cloud. Moreover, cloud architects who already have experience with other cloud providers and are now beginning to work with Google Cloud will benefit from the book. Although an intermediate-level understanding of cloud computing and distributed apps is required, prior experience of working in the public and hybrid cloud domain is not mandatory.
Building A Future Proof Cloud Infrastructure
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Author : Silvano Gai
language : en
Publisher: Addison-Wesley Professional
Release Date : 2020-02-13
Building A Future Proof Cloud Infrastructure written by Silvano Gai and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-13 with Computers categories.
Prepare for the future of cloud infrastructure: Distributed Services Platforms By moving service modules closer to applications, Distributed Services (DS) Platforms will future-proof cloud architectures—improving performance, responsiveness, observability, and troubleshooting. Network pioneer Silvano Gai demonstrates DS Platforms’ remarkable capabilities and guides you through implementing them in diverse hardware. Focusing on business benefits throughout, Gai shows how to provide essential shared services such as segment routing, NAT, firewall, micro-segmentation, load balancing, SSL/TLS termination, VPNs, RDMA, and storage—including storage compression and encryption. He also compares three leading hardware-based approaches—Sea of Processors, FPGAs, and ASICs—preparing you to evaluate solutions, ask the right questions, and plan strategies for your environment. Understand the business drivers behind DS Platforms, and the value they offer See how modern network design and virtualization create a foundation for DS Platforms Achieve unprecedented scale through domain-specific hardware, standardized functionalities, and granular distribution Compare advantages and disadvantages of each leading hardware approach to DS Platforms Learn how P4 Domain-Specific Language and architecture enable high-performance, low-power ASICs that are data-plane-programmable at runtime Distribute cloud security services, including firewalls, encryption, key management, and VPNs Implement distributed storage and RDMA services in large-scale cloud networks Utilize Distributed Services Cards to offload networking processing from host CPUs Explore the newest DS Platform management architectures Building a Future-Proof Cloud Architecture is for network, cloud, application, and storage engineers, security experts, and every technology professional who wants to succeed with tomorrow’s most advanced service architectures.
Human Interaction And Emerging Technologies Ihiet Ai 2025 Artificial Intelligence And Future Applications
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Author : Tareq Z. Ahram
language : en
Publisher: AHFE Conference
Release Date : 2025-04-28
Human Interaction And Emerging Technologies Ihiet Ai 2025 Artificial Intelligence And Future Applications written by Tareq Z. Ahram and has been published by AHFE Conference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-28 with Education categories.
Human Interaction and Emerging Technologies (IHIET-AI 2025): Artificial Intelligence and Future Applications Proceedings of the 13th International Conference on Human Interaction & Emerging Technologies: Artificial Intelligence & Future Applications, Costa Del Sol, Universidad de Málaga, Malaga, Spain, April 22-24,
Artificial Intelligence And Machine Learning In Management Science Emerging Research And Applications
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Author : Ms. Meenu Shukla
language : en
Publisher: NC Publishers
Release Date : 2025-07-01
Artificial Intelligence And Machine Learning In Management Science Emerging Research And Applications written by Ms. Meenu Shukla and has been published by NC Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Antiques & Collectibles categories.
As the global business environment continues to evolve, artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools for enhancing decision-making, optimizing operations, and fostering innovation across various sectors. This book brings together a collection of scholarly contributions from researchers and practitioners who are at the forefront of integrating these technologies with managerial practices. The chapters offer both theoretical insights and practical applications, covering domains such as operations research, strategic planning, supply chain optimization, marketing analytics, financial forecasting, and human resource management.
Essential Solutions Architect S Handbook
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Author : Bikramjit Debnath
language : en
Publisher: BPB Publications
Release Date : 2025-04-30
Essential Solutions Architect S Handbook written by Bikramjit Debnath and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-30 with Computers categories.
DESCRIPTION In an era where cloud computing, AI, and automation are reshaping industries, this book offers a comprehensive guide for IT professionals seeking to master modern software architecture. It will help bridge the gap between technical expertise and strategic leadership, empowering developers and mid-career professionals to stay ahead in an AI-driven, cloud-first world. Structured into six categories, this book covers key areas such as cloud foundations and migration, modern application development, and AI and advanced technologies. Readers will learn strategies for seamless cloud migration, microservices, serverless computing, and real-time data processing. This book will also provide insights into AI architecture, MLOps, and cloud data warehousing. The book’s focus on infrastructure automation, observability, and FinOps ensures operational efficiency while preparing you for future technological trends like hybrid/multi-cloud strategies, quantum computing, and sustainable IT practices. After reading this book, readers will have gained practical skills in cloud architecture, AI deployment, and data-driven decision-making. With strategic insights and industry best practices, they will be well-equipped to take on leadership roles such as solution architect, enterprise architect, or CTO, driving innovation and shaping the future of technology in their organizations. WHAT YOU WILL LEARN ● Understand solution architecture principles and design scalable solutions. ● Learn cloud migration strategies, including data center and application assessments. ● Explore modern application design practices like microservices and serverless. ● Master data management, governance, and real-time data processing techniques. ● Gain insights into generative AI, AI operationalization, and MLOps. ● Automate infrastructure with IaC, observability, and site reliability engineering. WHO THIS BOOK IS FOR This book is designed for experienced cloud engineers, cloud developers, systems administrators, and solutions architects who aim to expand their expertise toward a CTO-level understanding. It is perfect for professionals with intermediate to advanced knowledge of cloud technologies, systems architecture, and programming, seeking to elevate their strategic and technical skills. TABLE OF CONTENTS 1. Introduction to Solution Architecture 2. Cloud Migration Essentials 3. Operational Excellence in Cloud 4. Modern Application Architecture 5. Development Practices and Tools 6. Data Architecture and Processing 7. Data Strategy and Governance 8. Advanced Analytics 9. Generative AI and Machine Learning 10. Automation and Infra Management 11. FinOps Foundations 12. Security, Privacy, and Ethics 13. Innovation and Future Technologies 14. CTO’s Playbook for Transformation APPENDIX: Additional Resources for Further Learning
Ethical Considerations And Bias Detection In Artificial Intelligence Machine Learning Applications
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Author : Jayesh Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-10
Ethical Considerations And Bias Detection In Artificial Intelligence Machine Learning Applications written by Jayesh Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-10 with Computers categories.
At a time when artificial intelligence (AI) and machine learning (ML) are used to make sensitive societal decisions such as the ones related to criminal justice, healthcare, finance, education, employment, algorithmic fairness and bias mitigation are among the most important but challenging issues at hand. The goal of this book is to provide a holistic view across various disciplines of the ethical base, detection methods, and technical measures for trustworthy AI systems. Starting from a solid foundation of statistical bias, transparency systems and fairness-aware ML models, this book methodically looks at state-of-the-art methodologies, where we highlight their shortcomings and introduce a unified model framework for detecting bias and transparent algorithms. Moving beyond technical diagnoses, it examines key sociotechnical and policy tools that are required to implement AI responsibly, providing guidance to researchers, engineers, policy makers, and organizational leaders. Literature review has been driven following the experimental case, the fairness trade-offs, intersectional bias, explainability and regulatory compliance are discussed in depth by the authors. This work underscores that fairness in automated decision-making systems depends not only on algorithmic accuracy, but also institutional will and stakeholder engagement. The chapters in this book function as both an academic primer and a resourceful handbook, transitioning readers through an ever-growing ethical AI terrain. Whether you are a data scientist building and deploying an algorithm that encourages ethical speech, or a regulator working to create and refine guidelines around such algorithms, this book provides you with both the tools and the understanding you need for ethical technology development and deployment.