Managing Distributed Cloud Applications and Infrastructure

Managing Distributed Cloud Applications and Infrastructure
-0 %
A Self-Optimising Approach
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Artikel-Nr:
9783030398620
Veröffentl:
2020
Einband:
HC runder Rücken kaschiert
Erscheinungsdatum:
21.07.2020
Seiten:
188
Autor:
Theo Lynn
Gewicht:
363 g
Format:
216x153x15 mm
Serie:
Palgrave Studies in Digital Business & Enabling Technologies
Sprache:
Englisch
Beschreibung:

Theo Lynn is Full Professor of Digital Business at DCU Business School, Ireland and Director of the Irish Institute of Digital Business.

John G. Mooney is Associate Professor of Information Systems and Technology Management at the Pepperdine Graziadio Business School, United States.

Jörg Domaschka is Senior Researcher and Group Manager at the Institute of Information Resource Management at Ulm University, Germany and Coordinator of the Horizon 2020 RECAP project.

Keith A. Ellis is Senior Research Scientist and Manager of Intel Labs Europe, Ireland.

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 qualityof 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. 



Explores the use of novel technologies in reliable capacity provisioning across distributed clouds

Chapter 1.- Towards an Architecture for Reliable Capacity Provisioning for Distributed Clouds.- Chapter 2.- RECAP Data Acquisition and Analytics Methodology.- Chapter 3 - Application Optimisation: Workload Prediction and Autonomous Autoscaling of Distributed Cloud Applications.- Chapter 4 - Application Placement and Infrastructure Optimisation.- Chapter 5 - Simulating Across the Cloud-to-Edge Continuum.-  Chapter 6 - Case Studies in Application Placement and Infrastructure Optimisation.

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