Diego Pacheco Tech blog

Distributed Monoliths are the predominant form of modern legacy systems. Sometimes distributed monoliths are created by teams misapplying microservices architecture due to lack of isolation or internally shared libraries break of isolation. Other times, there is just the proverbial no time to refactor. Let's share the database. However, sometimes distributed monoliths happen due to non-obvious reasons from decisions that, at first glance, sound like good ideas and are even far away from engineering.  In software, we often run a trade-off analysis, Build vs Buy, where we must decide whether to build or buy software. Buying is usually attractive because it gives some speed (since you don't need to code it). Building, of course, takes longer, and you will need to maintain it; there is a chance of the project failing, and you invest money and have no software. There are trade-offs between building and buying. However, people often think buying has no implications and is much better...

No matter what programming languages you use. Engineers need to make dozens to hundreds of small decisions every day. Such decisions can sometimes save us and, other times, create many problems. Some of these decisions can be called assumptions. Depending on the context, they could be the side-effect, lack of proper discovery, feature factory rushing to delivery, or lack of care. In reality, error handling is one of the most challenging things in computer science, alongside naming, cache invalidation, and off-by-one errors. We usually get error handling wrong. When we are supposed to throw an error/exception and crash the application, we are unlikely to return some bad, sneaky default that will produce a bug down the road; when we need to ignore missing information, we end up crashing the app. Code reviews rarely to never review error handling. It's common to see services in production that don't even have the proper exception track due to improper error logging. Error handling...

Services are a very important architectural construct. Proper services( POSAM definition and principles) are even more important. However, not all services are the same. Not all APIs are the same, and definitely not all services are the same. Just having a Service or API, we can call it many different ways; the question is how good it is and how solid it is. I still put my money where my mouth is and say that services are a very powerful concept and the right level of abstraction for most problems. However, when a service is presented to you, you cannot assume you will have high quality just because it's a service. IF services are desired, multiple services must still be desired; after all, service orientation is about having services, not libraries. However, we know that when the granularity is wrong, and when we move data and capability to the wrong places, let's say, the wrong domain, we make things worse, not only risking breaking isolation but also leading to wrong abstra...