A good, although possibly expensive in terms of time and effort, test strategy is to simulate some or all of the components of our system. The reasons are multiple; on one hand, simulating or mocking software components allows us to test our interfaces to them more directly. In this respect, mock testing libraries, such as unittest.mock (part of the Python 3.5 standard library), are truly useful.

Another reason to simulate software components is to make them fail or misbehave on demand and see how our application responds. For instance, we could increase the response time of services such as REST APIs or databases, to worst-case scenario levels and see what happens. Sometimes, we might exceed timeout values in some network calls leading our application to incorrectly assume that the server has crashed.

Especially early on in the design and development of a complex distributed application, one can make overly optimistic assumptions about things such...