Microservice Pattern Identification from Recovered Architectures of Orchestrated Systems

Microservice architecture has become widely-used in industry, with tech giants like Amazon, Twitter, and LinkedIn leveraging microservices to evolve their web-scale applications. Microservice architecture brings benefits such as scalability and technological heterogeneity, although at a cost of complexity. A number of microservice patterns have been proposed to address this cost. This thesis explores the use of microservice patterns in recovered microservice architectures; however, there have been few attempts at recoveries of microservice systems. The contributions of this thesis are: 1. A definition of microservices as an architectural style, 2. A recovery technique for orchestrated systems which has been applied to three benchmark systems, and 3. A microservice pattern identification technique for five patterns, and applying it to the three recovered systems. In our results, 4 of the 5 patterns in all three benchmark systems were successfully identified