Anupama Raman – författare

Learn the importance of architectural and design patterns in producing and sustaining next-generation IT and business-critical applications with this guide.Key Features Use patterns to tackle communication, integration, application structure, and more Implement modern design patterns such as microservices to build resilient and highly available applications Choose between the MVP, MVC, and MVVM patterns depending on the application being builtBook Description Enterprise Architecture (EA) is typically an aggregate of the business, application, data, and infrastructure architectures of any forward-looking enterprise. Due to constant changes and rising complexities in the business and technology landscapes, producing sophisticated architectures is on the rise. Architectural patterns are gaining a lot of attention these days. The book is divided in three modules. You'll learn about the patterns associated with object-oriented, component-based, client-server, and cloud architectures. The second module covers Enterprise Application Integration (EAI) patterns and how they are architected using various tools and patterns. You will come across patterns for Service-Oriented Architecture (SOA), Event-Driven Architecture (EDA), Resource-Oriented Architecture (ROA), big data analytics architecture, and Microservices Architecture (MSA). The final module talks about advanced topics such as Docker containers, high performance, and reliable application architectures. The key takeaways include understanding what architectures are, why they're used, and how and where architecture, design, and integration patterns are being leveraged to build better and bigger systems.What you will learn Understand how several architectural and design patterns work to systematically develop multitier web, mobile, embedded, and cloud applications Learn object-oriented and component-based software engineering principles and patterns Explore the frameworks corresponding to various architectural patterns Implement domain-driven, test-driven, and behavior-driven methodologies Deploy key platforms and tools effectively to enable EA design and solutioning Implement various patterns designed for the cloud paradigmWho this book is for This book will empower and enrich IT architects (such as enterprise architects, software product architects, and solution and system architects), technical consultants, evangelists, and experts.

This practical text/reference provides an exhaustive guide to setting up and sustaining software-defined data centers (SDDCs). Each of the core elements and underlying technologies are explained in detail, often supported by real-world examples. The text illustrates how cloud integration, brokerage, and orchestration can ensure optimal performance and usage of data resources, and what steps are required to secure each component in a SDDC. The coverage also includes material on hybrid cloud concepts, cloud-based data analytics, cloud configuration, enterprise DevOps and code deployment tools, and cloud software engineering.Topics and features: highlights how technologies relating to cloud computing, IoT, blockchain, and AI are revolutionizing business transactions, operations, and analytics; introduces the concept of Cloud 2.0, in which software-defined computing, storage, and networking are applied to produce next-generation cloud centers; examines software-defined storage for storage virtualization, covering issues of cloud storage, storage tiering, and deduplication; discusses software-defined networking for network virtualization, focusing on techniques for network optimization in data centers; reviews the qualities and benefits of hybrid clouds, that bridge private and public cloud environments; investigates the security management of a software-defined data center, and proposes a framework for managing hybrid IT infrastructure components; describes the management of multi-cloud environments through automated tools, and cloud brokers that aim to simplify cloud access, use and composition; covers cloud orchestration for automating application integration, testing, infrastructure provisioning, software deployment, configuration, and delivery.This comprehensive work is an essential reference for all practitioners involved with software-defined data center technologies, hybrid clouds, cloud service management, cloud-based analytics, and cloud-based software engineering.

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Features: includes case studies and learning activities throughout the book and self-study exercises in every chapter; presents detailed case studies on social media analytics for intelligent businesses and on big data analytics (BDA) in the healthcare sector; describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data; examines real-time analytics solutions; introduces in-database processing and in-memory analytics techniques for data mining; discusses the use of mainframes for handling real-time big data and the latest types of data management systems for BDA; provides information on the use of cluster, grid and cloud computing systems for BDA; reviews the peer-to-peer techniques and tools and the common information visualization techniques, used in BDA.

This book presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. describes the network infrastructure requirements for effective transfer of big data, and the storage infrastructure requirements of applications which generate big data;