The monolithic layered architecture is one of the most common architectures in use across the software industry. Monolithic architectures are well suited for transaction-oriented enterprise applications that have well-defined features, change less often, and have complex business models. For such applications, transactions and consistency are of prime importance. They require a database technology with built-in support for ACID properties to store transactions. On the other hand, microservices are suited better for Software-as-a-Service, internet-scale applications that are feature-first applications with each feature focused on a single business capability. Such applications change rapidly and are scaled partially per business capability on demand. Transactions and consistency in such applications are hard to achieve due to multiple services, as compared to monoliths that are implemented as single applications.

It is recommended to start with a well designed, modular monolithic application irrespective of the domain complexity or transactional nature. Generally, all applications start as a monolithic application that can be deployed faster as a single artifact and later split into microservices when the application's complexity begins to outweigh the productivity of the team.

The productivity of the team may start decreasing when changes to the monolithic application start affecting more than one component, as shown in the preceding diagram. These changes may be a result of a new feature being added to the application, a database technology upgrade, or the refactoring of existing components. Any changes made to the application must keep the entire team in-sync, especially the deployment team, if there are any changes required in the deployment processes. Communicating such changes in a large team often results in a coordination nightmare, multiple change requests, and in-turn, reduces the overall productivity of the team working on the application.

Productivity also depends on the initial choices made with respect to the technology stack and its flexibility of implementation. For example, if a new feature requires a library that is readily available with a different technology stack or a programming language, it becomes challenging to adopt as it does not conform to the existing technology stack of the application components. In such cases, the team ends up implementing the same feature set for the current technology stack from scratch, and that in turn reduces productivity and further adds to the technology debt.