3 ms·

"Small" is a relative term, and not an ideal one, but what it generally means is "no larger than is needed" - that is, if you have one concrete solution within

"Small" is a relative term, and not an ideal one, but what it generally means is "no larger than is needed" - that is, if you have one concrete solution within a bounded context, "small" is the code necessary to implement that solution. It's not a matter of LOC. > IMO having everything self-contained to one repository I highly recommend keeping all microservices in a single repository. It's even more important in a microservice world to ensure that you can update dependencies across your organization atomically. > Horrible microservices that violate data boundaries, i.e. multiple services sharing a database which is a sadly common mistake, is a much harder problem to solve. But that's not microservices. Maybe this is in and of itself an issue of microservice architecture, the fact that people think they're implementing microservices when they're actually just doing SoA, but microservice architecture would absolutely not include multiple services with a single database, that would not be microservices. So I think the criticism would be "people find it hard to actually implement microservices" and not "microservice architecture leads to these problems", because microservice architecture is going to steer you away from multiple services using one database.

sally_glance 3y ago
A little off topic but there are even more sinister patterns than the shared database which some architects are actively advocating for, like 1. The "data service" layer, which (if done improperly) is basically just a worse SQL implemented on top of HTTP but still centralised. Though now you can claim it's a shared service instead of a DB. 2. The "fat cache" database - especially common in strongly event-based systems. Basically every service decides to store whatever it needs from events to have lower latency access for common data. Sounds great but in practice leads to (undocumented) duplicate data, which theoretically should be synchronised but since those service-local mirror DBs are usually introduced without central coordination it's bound to desync at some point.

sally_glance 3y ago

A little off topic but there are even more sinister patterns than the shared database which some architects are actively advocating for, like 1. The "data service" layer, which (if done improperly) is basically just a worse SQL implemented on top of HTTP but still centralised. Though now you can claim it's a shared service instead of a DB. 2. The "fat cache" database - especially common in strongly event-based systems. Basically every service decides to store whatever it needs from events to have lower latency access for common data. Sounds great but in practice leads to (undocumented) duplicate data, which theoretically should be synchronised but since those service-local mirror DBs are usually introduced without central coordination it's bound to desync at some point.