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Managing Distributed Cloud Applications and Infrastructure

The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum. The scale and complexity is si...

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Formato: Online
Idioma:inglês
Publicado em: Springer Nature 2021
Assuntos:
Innovation/Technology Management
e-Commerce/e-business
Computer Engineering
Business and Management
e-Commerce and e-Business
Computer Hardware
Analytics Models
Data Acquisition
Application Optimisation
Infrastructure
Distributed Clouds
digital business
Research & development management
Industrial applications of scientific research & technological innovation
Business applications
E-commerce: business aspects
Computer science
thema EDItEUR::K Economics, Finance, Business and Management::KJ Business and Management::KJM Management and management techniques::KJMV Management of specific areas::KJMV6 Research and development management
thema EDItEUR::U Computing and Information Technology::UF Business applications
thema EDItEUR::U Computing and Information Technology::UY Computer science
Acesso em linha:ONIX_20200813_9783030398637_17
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Resumo:The emergence of the Internet of Things (IoT), combined with greater heterogeneity not only online in cloud computing architectures but across the cloud-to-edge continuum, is introducing new challenges for managing applications and infrastructure across this continuum. The scale and complexity is simply so complex that it is no longer realistic for IT teams to manually foresee the potential issues and manage the dynamism and dependencies across an increasing inter-dependent chain of service provision. This Open Access Pivot explores these challenges and offers a solution for the intelligent and reliable management of physical infrastructure and the optimal placement of applications for the provision of services on distributed clouds. This book provides a conceptual reference model for reliable capacity provisioning for distributed clouds and discusses how data analytics and machine learning, application and infrastructure optimization, and simulation can deliver quality of service requirements cost-efficiently in this complex feature space. These are illustrated through a series of case studies in cloud computing, telecommunications, big data analytics, and smart cities.

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