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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. Dr. Pethuru Raj is Chief Architect of the Site Reliability Engineering (SRE) Division at Reliance Jio Infocomm Ltd. (RJIL), Bangalore, India. His other publications include the Springer titles Automated Workflow Scheduling in Self-Adaptive Clouds and (with Mrs. Raman) High-Performance Big-Data Analytics. Mrs. Anupama Raman works at Flipkart Internet India Pvt Ltd, Bangalore, India. .

Cloud computing --- Electronic data processing --- Software-defined networking (Computer network technology) --- Management. --- Distributed processing --- Computer science. --- Input-output equipment (Computers). --- Computer communication systems. --- Software engineering. --- Database management. --- Industrial organization. --- Computer Science. --- Computer Communication Networks. --- Input/Output and Data Communications. --- Software Engineering. --- Database Management. --- Industrial Organization. --- SDN (Computer network technology) --- Software-defined networks (Computer network technology) --- Computer networks --- Web services --- Data transmission systems. --- Industries --- Organization --- Industrial concentration --- Industrial management --- Industrial sociology --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Computer software engineering --- Engineering --- Data communication systems --- Transmission of data --- Digital communications --- Electronic systems --- Information theory --- Telecommunication systems --- Computer hardware --- Computer I/O equipment --- Computers --- Electronic analog computers --- Electronic digital computers --- Hardware, Computer --- I/O equipment (Computers) --- Input equipment (Computers) --- Input-output equipment (Computers) --- Output equipment (Computers) --- Computer systems --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Network computers --- Input-output equipment --- Computer networks. --- Computer input-output equipment.

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Internet of things.

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Learn the importance of architectural and design patterns in producing and sustaining next-generation IT and business-critical applications with this guide. About This Book 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 built Who 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. 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 paradigm In Detail 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. Style and Approach This book adopts a hands-on approach with re...

Software architecture.

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This important and timely text/reference presents a detailed review of high-performance computing infrastructures for next-generation big data and fast data analytics. Comprehensively covering a diverse range of computer systems and proven techniques for high-performance big-data analytics, the book also presents case studies, practical guidelines, and best practices for enabling decision-making toward implementing the appropriate computer systems and approaches. Topics and features: Includes case studies and learning activities throughout the book, and self-study exercises at the end of every chapter Presents detailed case studies on social media analytics for intelligent businesses, and on big data analytics 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, such as machine data analytics and operational analytics 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 big and fast data analytics Provides information on the use of cluster, grid and cloud computing systems for big data analytics and data-intensive processing Reviews the peer-to-peer techniques and tools, and the common information visualization techniques, used in big data analytics Software engineers, cloud professionals and big data scientists will find this book to be an informative and inspiring read, highlighting the indispensable role data analytics will play in shaping a smart future.

Electronics --- Office management --- Programming --- Computer architecture. Operating systems --- Information systems --- Computer. Automation --- microprocessoren --- applicatiebeheer --- apps --- informatica --- bedrijfsadministratie --- informatiesystemen --- computernetwerken --- architectuur (informatica)