Enterprise Devops Architecture From Legacy Systems To Cloud Native Platforms 2025
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Enterprise DevOps Architecture: From Legacy Systems to Cloud-Native Platforms 2025
Author: AUTHOR-1: SOURABH SANGHI, AUTHOR-2: DR AJAY KUMAR CHAURASIA
language: en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date:
PREFACE In an era defined by rapid technological change and mounting business pressures, organizations face the dual challenge of sustaining legacy systems while embracing the agility, scalability, and resilience of cloud-native platforms. Enterprise DevOps Architecture: From Legacy Systems to Cloud-Native Platforms offers a pragmatic roadmap for navigating this transformation. Drawing on real-world case studies, industry best practices, and the collective wisdom of DevOps pioneers, this volume illuminates how enterprises can evolve their IT foundations, integrate people and processes, and harness automation at scale. The journey begins by tracing the evolution of enterprise IT and explaining why traditional siloed approaches must give way to continuous delivery and iterative feedback loops. We then establish the core principles and pillars of enterprise DevOps, from collaboration and shared ownership to metrics-driven decision making and “shift-left” practices that embed quality and security throughout the development lifecycle. As many organizations wrestle with monolithic, mission-critical applications, Chapter 3 guides you through the assessment and migration of legacy systems. You’ll learn to evaluate technical debt, prioritize modernization strategies (Rehost, Refactor, Replat form, and more), and define a phased roadmap that minimizes disruption while maximizing business value. Transitioning to cloud-native architectures demands fresh design paradigms. In Chapter 4, we explore patterns such as microservices, containerization, and service meshes, detailing how they enable resilient, self-healing systems. Chapter 5 then dives into CI/CD pipelines at enterprise scale, illustrating techniques for parallel testing, blue-green and canary deployments, and strategies for scaling pipelines across thousands of services. Automation is the lifeblood of DevOps. Chapter 6 examines Infrastructure as Code—from declarative frameworks like Terraform and Pulu mi to idempotent configuration and policy-as-code. We demonstrate how to codify standards, enforce guardrails, and manage drift in dynamic environments. Security and compliance cannot be afterthoughts. Chapter 7 brings together DevSecOps practices, offering a blueprint for integrating vulnerability scanning, secrets management, and audit-friendly controls without slowing innovation. Building on that, Chapter 8 covers monitoring, observability, and SRE practices, showing how service-level objectives and error budgets drive reliability and continuous improvement. With a plethora of specialized tools available, Chapter 9 unpacks DevOps toolchain integration and orchestration, advising on how to select, connect, and govern tools for source control, build automation, artifact repositories, and beyond. Recognizing that technology alone cannot guarantee success, Chapter 10 addresses organizational change management—how to cultivate a culture of experimentation, distributed ownership, and relentless learning. Finally, Chapter 11 looks ahead to hybrid and multi-cloud DevOps strategies, where enterprises leverage the best attributes of public clouds, private data centers, and edge environments. We discuss network connectivity, data gravity, and policy consistency across heterogeneous landscapes. By the end of this book, practitioners, architects, and leaders will possess a comprehensive framework for transforming monolithic estates into agile, cloud-native platforms. Whether you’re just beginning your DevOps journey or seeking to elevate an existing practice to enterprise scale, the insights within will equip you to accelerate delivery, improve quality, and align technology investments with strategic business outcomes. Authors Sourabh Sanghi Dr Ajay Kumar Chaurasia
Cloud-Native Financial Systems: From Legacy to Real-Time Intelligence 2025
Author: AUTHOR-1: Vamsi Krishna Koganti, AUTHOR-2: Dr.Gauri Shanker Kushwaha
language: en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date:
PREFACE Cloud-Native Financial Systems: From Legacy to Real-Time Intelligence presents a comprehensive roadmap for transforming traditional financial infrastructures into agile, resilient, and intelligent systems using cloud-native principles. As the financial industry undergoes unprecedented digital disruption, institutions are compelled to modernize core systems, embrace real-time processing, and meet the growing demands for security, interoperability, and innovation. This book serves as a strategic and technical guide for IT leaders, cloud architects, developers, compliance officers, and financial technology professionals driving this transformation. The financial sector faces a dual challenge: retaining trust through reliability and compliance while accelerating the delivery of new, intelligent products in an increasingly competitive digital ecosystem. Traditional monolithic architectures, legacy batch processing systems, and siloed databases no longer meet the expectations of real-time insights, 24/7 accessibility, and scalable innovation. Cloud-native technologies—comprising containerization, microservices, serverless computing, API-first design, DevSecOps, and AI/ML—offer the foundation to not only re-architect aging platforms but also reimagine financial services for the future. This book is structured to follow the logical arc of digital transformation. Chapter 1 sets the stage with an introduction to the need and impact of cloud-native adoption in finance. Chapter 2 explores the constraints and opportunities within legacy systems. Chapter 3 details cloud architecture principles tailored to financial workloads. Chapter 4 and Chapter 5 dive into the technologies of containerization and real-time data processing. Chapter 6 emphasizes API-first design, while Chapter 7 tackles critical concerns around security, compliance, and governance. In Chapter 8, we explore the power of cloud-native data lakes in extracting financial intelligence. Chapter 9 explains DevOps and CI/CD strategies within highly regulated environments. Chapter 10 introduces intelligent automation through AI/ML, and finally, Chapter 11 focuses on business continuity, resilience, and observability as foundational pillars of trust and uptime. Whether you’re modernizing a legacy banking core, building fintech platforms from scratch, or engineering intelligent analytics pipelines, this book will help you understand not only what needs to change—but how to design, implement, and scale cloud-native systems that are compliant, scalable, and future-ready. Authors
Practical Data Engineering for Cloud Migration: From Legacy to Scalable Analytics 2025
Author: Author:1- Sanchee Kaushik, Author:1- Prof. Dr. Dyuti Banerjee
language: en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date:
PREFACE The exponential growth of data in today’s digital landscape has reshaped how businesses operate, forcing organizations to rethink their data strategies and technologies. As more companies embrace cloud computing, migrating legacy data systems to the cloud has become a critical step towards achieving scalability, flexibility, and agility in data management. “Practical Data Engineering for Cloud Migration: From Legacy to Scalable Analytics” serves as a comprehensive guide for professionals, data engineers, and business leaders navigating the complex but transformative journey of migrating legacy data systems to modern cloud architectures. The cloud has emerged as the cornerstone of modern data infrastructure, offering unparalleled scalability, on-demand resources, and advanced analytics capabilities. However, the transition from legacy systems to cloud-based architectures is often fraught with challenges—ranging from data compatibility issues to migration complexities, security concerns, and the need to ensure that the newly integrated systems perform optimally. This book bridges that gap by providing practical, real-world solutions for overcoming these challenges while focusing on achieving a scalable and high-performing data environment in the cloud. This book is designed to guide readers through every aspect of the cloud migration process. It starts by addressing the core principles of data engineering, data modeling, and the basics of cloud environments. From there, we delve into the specific challenges and best practices for migrating legacy data systems, transitioning databases to the cloud, optimizing data pipelines, and leveraging modern tools and platforms for scalable analytics. The chapters provide step-by-step guidance, strategies for handling large-scale data migrations, and case studies that highlight the successes and lessons learned from real-world cloud migration initiatives. Throughout this book, we emphasize the importance of ensuring that cloud migration is not just a technical task but a strategic business decision. By providing insights into how cloud migration can unlock new opportunities for data-driven innovation, this book aims to empower organizations to make informed decisions, harness the full potential of their data, and move towards more efficient and scalable cloud-native analytics solutions. Whether you are an experienced data engineer tasked with migrating legacy systems or a business leader looking to understand the strategic value of cloud data architectures, this book will provide you with the knowledge and tools necessary to execute a successful cloud migration and set your organization up for future growth. Authors