Pattern-based multi-cloud architecture migration

Many organizations migrate on-premise software applications to the cloud. However, current coarse-grained cloud migration solutions have made such migrations a non transparent task, an endeavor based on trial-anderror. This paper presents Variability-based, Pattern-driven Architecture Migration .V-PAM), a migration method based on (i) a catalogue of fine-grained service-based cloud architecture migration patterns that target multi-cloud, (ii) a situational migration process framework to guide pattern selection and composition, and (iii) a variability model to structure system migration into a coherent framework. The proposed migration patterns are based on empirical evidence from several migration projects, best practice for cloud architectures and a systematic literature review of existing research. Variability-based, Pattern-driven Architecture Migration allows an organization to (i) select appropriate migration patterns, (ii) compose them to define a migration plan, and (iii) extend them based on the identification of new patterns in new contexts. The patterns are at the core of our solution, embedded into a process model, with their selection governed by a variability model

Data Migration in Cloud: A Systematic Review

Data migration needs to  securely transfer for maintaining confidentiality such that migration can strongly and effectively done with no data loss due to active attacks . Many techniques and methods have already been proposed by researchers around the world to secure data migration. This paper provides a critical overview of these problems and solutions and giving a proposed solution for data migration that is Attunity which can help to optimize data for replicating and transferring data thus providing a simple, faster and safer path to accelerate data by providing

Component-aware Orchestration of Cloud-based Enterprise Applications, from TOSCA to Docker and Kubernetes

Enterprise IT is currently facing the challenge of coordinating the management of complex, multi-component applications across heterogeneous cloud platforms. Containers and container orchestrators provide a valuable solution to deploy multi-component applications over cloud platforms, by coupling the lifecycle of each application component to that of its hosting container. We hereby propose a solution for going beyond such a coupling, based on the OASIS standard TOSCA and on Docker. We indeed propose a novel approach for deploying multi-component applications on top of existing container orchestrators, which allows to manage each component independently from the container used to run it. We also present prototype tools implementing our approach, and we show how we effectively exploited them to carry out a concrete case study

Middleware Patterns for Cloud Platforms

This chapter explores how traditional system architectures are being affected by the emergence of ‘Uber’ style platform models that provide business services with huge global reach. The specific demands and characteristics of such platforms are discussed which in turn dictate their technical requirements. The chapter will explain how middleware technologies have evolved to support today’s requirements for such massively scalable platform solutions. The latest preferred architectural paradigms dictate the use of micro-services and APIs are central to the design of such platforms. Similarly, event based architectures are another key paradigm that must be supported. The role of modern middleware and cloud technologies to support these newly dominant paradigms will be explained. Key architectural patterns pertinent to global platform solutions are illustrated. The role of modern middleware in fulfilling these patterns is highlighted using real-world examples from the field of open finance

Strategies for Cloud Services Adoption in Saudi Arabia

The adoption rate of cloud computing is low among business organizations in Saudi Arabia, despite the cost-saving benefits of using cloud services. The purpose of this multiple case study was to explore the strategies that information technology (IT) leaders in the manufacturing industry in Saudi Arabia used to adopt cloud computing to reduce IT costs. The target population of this study consisted of 5 IT leaders from 5 different manufacturing companies in Saudi Arabia who successfully adopted cloud computing in their companies to reduce IT costs. Rogers\u27s diffusion of innovation theory was the conceptual framework for this research. Data collected from face-to-face, semistructured interviews and a review of relevant corporate documentation were analyzed using Yin\u27s 5-step data analysis method, which included compiling, disassembling, reassembling, interpreting, and concluding the data. Five themes emerged from the data analysis: identify business needs and requirements, apply value realization metrics, plan for migration, choose the right cloud service provider, and provide adequate training and awareness sessions. The implications of this study for positive social change include the potential to improve the local economy in Saudi Arabia by ensuring the sustainability of firms in the manufacturing industry through the implementation of cost-saving strategies associated with cloud computing adoption