Enter… data mesh
To begin our architecting exercise, we needed to understand how to group data and functions into cohesive services to support our various product lines, anticipating the need for data sharing. We decided to follow the data mesh approach, a concept developed by ThoughtWorks’ Zhamak Dehghani, starting with Domain Driven Design (DDD).
With our first architecture designs, we quickly realized that we would likely have to deal with dozens of services to provide all the functionality of our product portfolio. As a result, the concept of bounded context proved to be critical. Bounded context allows for identification of models interrelated due to their common presence in related business needs. We can then identify touchpoints in between contexts, possibly surfacing through concepts with similar semantics in adjacent capabilities. By extrapolating data models to functions and services, bounded context helps group functions based on context and utility: those that manipulate the same data and have frequent interactions, functions that are bridging data flows in between contexts, and unrelated functions.
From this view (fully acknowledging Conway’s law), it becomes easier to attain organizational alignment even as our organization is constantly evolving. It becomes easier to identify team ownership on a set of services and make organizational decisions without performing major rewrites of our services. We also gain a better understanding of runtime coupling in between services, and can start applying governance on the interconnection points.
A simplified, partial decomposition of our DDD model with three identified bounded contexts could be defined as follows for our secure and compliant collaboration services: