Model-Based Application Deployment on Cloud Computing

Model-Based Application Deployment on Cloud Computing

Aouat Asmaa (University of Oran1 Ahmed Ben Bella, Laboratory of Parallel, Embedded Architectures and High Performance, Oran, Algeria), Deba El Abbassia (University of Oran1 Ahmed Ben Bella, Laboratory of Parallel, Embedded Architectures and High Performance, Oran, Algeria), Benyamina Abou EL Hassan (University of Oran1 Ahmed Ben Bella, Laboratory of Parallel, Embedded Architectures and High Performance, Oran, Algeria) and Benhamamouch Djilali (University of Oran1 Ahmed Ben Bella, Laboratory of Parallel, Embedded Architectures and High Performance, Oran, Algeria)
Copyright: © 2019 |Pages: 18
DOI: 10.4018/IJDST.2019040106

Abstract

Cloud Computing refers to a set of technologies and systems that provide various types of resources (computing, storage, software, etc.) on demand, through the Internet or Intranet. Thanks to these advantages many Cloud providers are available and is increasing. These cloud providers offer different PaaS platforms that must each be configured in its own appropriate way to deploy applications in the cloud. Cloud Computing is based on heterogeneity principles, which allows many configurations and sizing choices. This implies that the developer must master all deployment methods in order to benefit from all suppliers. The development and deployment of applications in the Cloud offers a new scientific challenge in terms of expression and taking into account variability. The purpose of the author's work is to propose a deployment method and implement it to automate the process of deploying applications in a cloud environment based on model-driven engineering, to configure and provision applications to be deployed in the cloud.
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Many efforts have been made to help developers deploy and manage their applications on heterogeneous PaaS and IaaS platforms. These efforts are presented in APIs form and could be organized into three categories. These categories depend on approaches (Talwar et al., 2005) on which the majority of deployment APIs are based.

Many tasks in the management of systems and application operations are already automated using scripts. These scripts are usually copied by hand to the target system on which they are executed. Compared to plans, these scripts can be considered micro-flows: small isolated jobs that can be executed quickly and do not require transactional support (Szyperski, 2003). This type of approach reduces the risk of human error during the manual deployment process, and for the developer, the developer takes care of application development instead of a cloud computing configuration.

This type of approach reduces the risk of human error during the manual deployment process, and for the developer, the developer takes care of application development instead of a cloud computing configuration. Generally, when applications are small or system configurations rarely change, the script approach is the reasonable solution. Among the works that have adopted this approach is the work of MUTIARA (Mutiara et al., 2014).

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