When you start the development of an application you often spend a significant amount of time writing the build logic and putting in place the mechanisms to handle cross-cutting concerns. The build logic builds, and tests the application and also packages into a production-ready format, such as a Docker container image. For example, the majority of the build logic for a Java application is implemented using Gradle or Maven. It might also consist of configuration scripts for build automation tool, such as CircleCI or Github Actions. On the surface, the build logic appears to be quite simple. However, even defining a carefully curated set of dependencies can be remarkably challenging.
In addition to the build logic, you need to handle cross cutting concerns. Examples of cross-cutting concern include:
As well as these generic cross-cutting concerns, there are also cross-cutting concerns that are specific to the technologies that an application uses. Applications that use infrastructure services such as databases or a message brokers require boilerplate configuration in order to do that. For example, applications that use a relational database must be configured with a connection pool. Web applications that process HTTP requests also need boilerplate configuration.
It is common to spend one or two days, sometimes even longer, writing the build logic and implementing cross-cutting concerns. If you going to spend months or years developing a monolithic application then the upfront investment is insignificant. The situation is very different, however, if you are developing an application that has the microservice architecture. There are tens or hundreds of services. You will frequently create new services, each of which will only take days or weeks to develop. You cannot afford to spend a few days setting up every service. What is even worse is that in a microservice architecture there are additional cross-cutting concerns that you have to deal with including service registration and discovery, and circuit breakers for reliably handling partial failure.
Create a source code template that a developer can copy in order to quickly start developing a new service. A template is a simple runnable service that implements the required build logic and cross cutting concerns along with sample application logic.
This pattern has the following benefits:
This pattern has the following drawbacks:
This pattern has the following issues:
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