When computers were more centralized, connected services could be done in a linear sequential pattern. However, as we enter the cloud era of computing, event driven architecture (EDA) becomes ubiquitous. EDA allows for multiple events and data exchanges to happen at the same time. From real time chat to stock price changes, EDA is commonplace in modern day applications.
The Reactive Manifesto highlights the advantages for EDA (Bonér et al.). For one thing, the systems are much more responsive. Responsiveness helps to detect problems quickly and creates more confidence for the users. The systems are resilient; failures are contained and isolated. The resources allocated determine its elasticity and scalability.
EDA can still run into problems dependent on the system. For example, in a monolithic system, it becomes more difficult to test new features or make changes fast (Zhelev & Rozeva, 2019). Updating new technologies could be made more difficult because of different languages or framework versions. In microservices, an initial investment can be large because it takes time to interconnect the different microservices and make sure the architecture is clean (Zhelev & Rozeva, 2019).
EDA has different applications. In a data distribution service (DDS), messages can be relayed centrally to different pipelines at one time (Dunkel et al., 2011). Traffic report systems can use domain data and raw sensor data to transmit road conditions. This information is relayed for diagnosis and steps can be taken to reroute traffic. All modern data web applications use EDA, whether that be Walmart’s shopping website or Facebook.
EDA has been commonplace for a while and will continue to play a role as we move to cloud based systems. EDA’s ability to process continuous data will help connect different devices and systems. In healthcare, we are constantly monitoring the body’s changing system and trying to make sense of the data. EDA is perfect for data that is constantly changing.
References
Bonér, Jonas, et al. “The Reactive Manifesto.” The Reactive Manifesto, 16 Sept. 2014, www.reactivemanifesto.org/. Accessed 16 Aug. 2020.
Dunkel, J., Fernández, A., Ortiz, R., & Ossowski, S. (2011). Event-driven architecture for decision support in traffic management systems. Expert Systems With Applications, 38(6), 6530–6539. https://doi.org/10.1016/j.eswa.2010.11.087
Zhelev, S., & Rozeva, A. (2019). Using microservices and event driven architecture for big data stream processing. AIP Conference Proceedings, 2172(1). https://doi.org/10.1063/1.5133587