Modelling and simulating the scalability of e-commerce web application architectures

The e-commerce turnover has a constant growth rate of about 10%. An additional increase in complexity and traffic spikes clarify the need for a scalable software architecture to prevent a potential technical debt, higher financial cost, longer maintenance, or a reduced reliability. Due to the fact, that existing approaches like the Palladio Approach require a high modelling overhead and the importance of dropping this overhead was identified this master thesis is focused on the modelling and simulation of e-commerce web application architectures using a high-level approach to provide a faster, but possibly more inaccurate prediction of the scalability. This is done by the usage of the Design Science Research Process as a frame, a scientific literature review for use of the existing knowledge base and the Conical Methodology for the artefact creation. The artefact is a graphical model which is evaluated using a simulation developed with Python and its framework SimPy. For model creation and evaluation a total of twelve papers investigating the scalability of e-commerce web application architectures is split into a test and train group. The training group and parts of the scientific research are used to identify the components load balancer, application server, web tier, ERP system, legacy system and database as well as some general characteristics that need to be considered. The components with the most modelling variables are the application server and web tier with a total of thirteen, while the ERP and legacy system only required five. The model is evaluated using a total of three papers from the test group, where an average throughput error of 5.78% and a response time error of 46.55% or 26.46% was identified. An additional evaluation based on two non-e-commerce architectures shows the usability of the model for other types of architectures. Even though the average error gives the impression, that the model is not providing a good estimation, the graphical results show, that the model and its simulation can be used to provide a faster scalability prediction. The model is least accurate for the prediction of the situation, where the response time increases exponentially, as this is the point, where variables, only accountable for some percentage and thus ignored for the model, have the highest influence. Future research can be found in the extension of the model by either adding or investigating additional components, adding features ignored within this work or applying it to other types of web application architectures. Additionally, both the low-level and the high-level approaches can be brought together to combine the advantages from both approaches