Abstract:Features or functionalities provided by cloud-based applications are accessed by users through various interfaces such as web browser, mobile app, and command line interface. Yet for monitoring cloud-based applications, software developers and researchers have focused on web browsers. Software updates are provided for such applications based on the data acquired from the cloud monitoring components but usage data of the cloud application features are difficult to extract in a cloud environment as the usage data is spread across the interfaces on the front-end and the back-end. In this paper, we focus on the usage of the cloud application features from the user perspective and how to extract these data in a cloud environment. We define six criteria for the user-level usage data, analyse the existing usage data extraction techniques and propose a usage data extraction framework adhering to the defined criteria.
Cloud migration has attracted a lot of attention in both industry and academia due to the on-demand, high availability, dynamic scalable nature. Organizations choose to move their on-premise applications to adapt to the virtualized environment of the cloud where the services are accessed remotely over the internet. These applications need to be re-engineered to completely exploit the cloud infrastructure such as performance and scalability improvements over the on-premise infrastructure. This paper proposes a re-engineering approach called architectural refactoring for restructuring on-premise application components to adopt to the cloud environment with the aim of achieving significant increase in non-functional quality attributes such as performance, scalability and maintainability of the cloud architectures. This paper proposes, when needed to migrate to cloud, the application is divided into smaller components, converted into services and deployed to cloud. The paper discusses existing issues faced by software developers and engineers during cloud migration, introduces architectural refactoring as a solution and explains the generic refactoring process at an architectural level.
Usage in the software field deals with knowledge about how end-users use the application and how the application responds to the users' action. Understanding usage data can help developers optimise the application development process by prioritising the resources such as time, cost and man power on features of the application which are critical for the user. However, in a complex cloud computing environment, the process of extracting and analysing usage data is difficult since the usage data is spread across various front-end interfaces and back-end underlying infrastructural components of the cloud that host the application and are of different types and formats. In this paper, we propose usage analytics, a process to extract and analyse usage to understand the behavioural usage patterns of the user with the aim to identify features critical to user. We demonstrate how to identify the features in a cloud based application, how to extract and analyse the usage data to understand the user behaviour.
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