Comparing Monolithic and Event-Driven Architecture when Designing Large-scale Systems

Sammanfattning: The way the structure of systems and programs are designed is very important. When working with smaller groups of systems, the chosen architecture does not affect the performance and efficiency greatly, but as these systems increase in size and complexity, the choice of architecture becomes a very important one. Problems that can arise when the complexity of software scales up are waiting for data accesses, long sequential executions and potential loss of data. There is no single, optimal software architecture, as there are countless different ways to design programs, but it is interesting to look at which architectures perform the best in terms of execution time when handling multiple bigger systems and large amounts of data. In this thesis, a case called "The Income Deduction" will be implemented in a monolithic and an event-driven architectural style and then be put through three different scenarios. The monolithic architecture was chosen due to its simplicity and popularity when constructing simpler programs and systems, while the event-driven architecture was chosen due to its theoretical benefits of removing sequential communicating between systems and thus reduce the time systems spend waiting for each other to respond. The main research question to answer is what the main benefits and drawbacks are when building larger systems with an event-driven architectural style. Additional research questions include how the architecture affects the organisation’s efficiency and cooperation between different teams, as well as how the security of data is handled. The two implementations where put through three different scenarios within the case, measuring execution time, number of HTTP requests sent, database accesses and events emitted. The results show that the event-driven architecture performed 9.4% slower in the first scenario and 0.5% slower in the second scenario. In the third scenario the event-driven architecture performed 49.0% faster than the monolithic implementation, finishing the scenario in less than half the amount of time. The monolithic implementation generally performed well in the simpler scenarios 1 and 2, where the systems had fewer integrations to each other. In these cases it is the preferred solution since it is easier to design and implement. The event-driven solution did perform much better in the more complex scenario 3, where a lot of systems and integrations were involved, since it could remove certain connections between systems. Lastly, this thesis also discusses the sustainability and ethics of the study, as well as the limitations of the research and potential future work.