I'm breaking my system into (at least) two bounded-contexts: study-design and survey-planning.
There's a concept named "subject" (potential subject for interviewing) in the study-design context. We also maintain associations between subjects and populations in that domain.
Now, in the survey-planning, we also need (some) information about the subject (for example: for planning a visit, or even for anticipated selection of questionnaire, in case the population the subject belongs to is known beforehand).
So, I need that "subject" in both contexts.
What approach should I pick? Having a shared kernel, as explained in Eric Evans DDD book? I don't mind (at least for now) having the two contexts sharing the same database.
Or... should I go pure microservice? Meaning: those two can't / shouldn't share database..., and in that case I might have to go the mirroring / duplicating route through event passing: https://www.infoq.com/news/2014/11/sharing-data-bounded-contexts
Any thoughts on which one is better, for the above situation?
Thanks!
The context for microservices is distributed systems. In any other situation it would probably be overkill. Shared kernel will eventually split. That is usually the case. You may start from it. Nothing wrong with that. However, it will not stay there.
In my opinion, you have three entities:
- study
- survey
- person
It is pretty intuitive to see that each of these is its own aggregate root. So then we are talking about inter-root relationships. In my experience, those are meaningful entities on their own, and cleanest and most future proof by far is to treat those relationships as independent aggregate roots.
The relationship between a study and a person is perhaps called TestSubject, and the relationship between a person and a survey could be called Interviewee or something similar. In another context, the person could be an employee for a company, and then the Employee would be its own aggregate root. Information that only relates to the relationship and not to the person or the study say, should be limited to this relationship specific aggregate root. This could for instance be the start date at which the subject started to take part in the test, and the end date (when he dropped out, if he or she dropped out prematurely, etc.)
As for storage, all aggregate roots should define their own separate repositories as interfaces and know only those interfaces, but the implementation of those interfaces is free to choose to use the same database or different ones, or even different kinds, local or distributed, etc. So this holds for these 'relational' aggregate roots as well. But you should almost force yourself to use different databases and preferably even different technologies (e.g. one EntityFramework, the other MongoDb) when you start with this, to force yourself to make sure your interfaces are properly defined and independent of implementation.
And yes, big fan of CQRS as well here, and Event/Command Sourcing as well. There are many light-weight implementations possible that allow you to upscale, but are very easy to get into and afford you almost completely linear (=predictable) complexity.
I recommend that you choose a event-driven solution, but not necessarily to use microservices. You could build an event-driven monolith in order to spend much less time on synchronizing the two models. When the application grows too big then you split the monolith into microservices. You could use CQRS to split event more the models into write and read. If you use event-sourcing things get even more interesting.
In my experience, with shared kernel, the models become god objects, one-size-fits-all kind of objects.
来源：https://stackoverflow.com/questions/42562820/ddd-shared-kernel-or-pure-event-driven-microservices