Data Analytics And Application Life Cycle Development Using Gulp Task Runners

Abstract

In application life cycle model, there are many repetitive tasks to be performed right from development stage up to the application usage stage. Each task involves human effort and time though being routine in nature. This then impacts the cost and time for application life cycle. It is must be noted that application development cost also includes the testing phase cost in the application life cycle. It is very important for any application life cycle to fine tune this operation model and thereby lower the cost. In other use cases, when the application is deployed for usage, the application may involve network related operations whereby it may interact with local controller in a subnet or a remote controller. In such use cases, the response time of application while it accesses the controller plays an important role in quality of application. The network traffic problem over the internet is a formidable problem in the world of networked devices where different devices such as IoT devices have exploded in the network. Gulp task runner helps in the automation of all repetitive tasks that can be usually employed systematically in application life cycle from development to application usage stage. It is accepted that such automation can save significant human effort and eliminate errors and thereby reduce testing costs. We believe that with automated task runners used in application life cycle, we can demonstrate savings in effort and cost and thus focus our effort more to analyze the application usage involving data traffic, failure analysis and accordingly adapt with corrective actions such as improving the throughput of the whole system.