Have you ever been asked to take part in a taste test or in a private focused group discussion before an item was set to be released in the market? The same principle applies for an Application Program Interface (API) that are being developed as part of a business’s core services—before you release the finished product for use among your customers, you’d like to work out all the kinks.
APIs undergo several steps of development before their full virtualization or the completion of a virtual copy mirroring all the specifications of production. One of those steps is termed API mocking, in which a team of developers works with imitation software components that emulate their real counterparts’ behavior in specific contexts.
For this feature, let’s define API mocking, discuss where it fits into completing a simulation of an API, what you can achieve for your API’s development during the mocking stage, and why open API mocking is currently the trend among today’s developers. Let’s check out the role that mocking plays in enhancing your API.
API Mocking and Its Related Steps in Simulation
In the grand scheme of things, it is neither practical nor efficient to skip right to the API virtualization stage. API mocking and API virtualization are two different rungs on the upward ladder of API simulation, so the terms are not meant to be used interchangeably.
The two fit in a sequence for creating an API simulation that typically unfolds like this:
- Stubbing stage. This is when developers create and work with a placeholder virtual part that does not have any real functionality;
- Mocking stage. This is when developers create parts with basic functionality that is required only for a specific testing or development purpose;
- Simulation stage. This is when developers construct virtual parts that have complete functionality for testing or development purposes, and;
- Virtualization stage. This is when the API simulation in question may be deployed into an operational, manageable, and controllable environment.
Mocks can be done at several levels, such as for coding, service, and infrastructure. Regardless, they are meant to elicit a particular behavioral response in order to fulfill a certain development need at a specific time. As such, mocks can be run in isolation from the rest of the API components that are being tested, and it can be repeated as many times as deemed necessary by the developers.
A typical setup for mocking is a singular server that can match certain request returns. From these mocks, developers can obtain feedback quickly from a manual or automated test, diagnose and fix bugs, and achieve consistent results.
Overall, the mocking stage can be extremely helpful and productive for a team of developers working in tandem before the API’s visualizations. It is at the mocking stage where developers can recognize all the development and testing workflows possible—and this increases their agility in engaging with increasingly complex infrastructures and systems.
Common Mocking Scenarios and Best Practices to Deploy at the Mocking Stage
The rationale behind mocking is the developer’s capacity to test components accurately in particular contexts—all without the need for external dependencies. This enables development for the API even when full access to target systems is difficult, forbidden, restricted, or plainly impossible because the means to do so are nonexistent. The team doesn’t develop code with the actual external dependencies in place but creates mock dependencies to use instead.
In many cases, these mocks can still be intelligent enough to help developers call accurate shots, and deduce how to move forward based on results that are similar to the actual components. This is how, in the absence of a “real” testing ground with the external dependencies, developers can still push through on the API’s milestones.
Better yet, today’s technologies are well-suited to a lot of play in the mocking stages. A mechanism like open API mocking enables developers to share a platform for testing, create mocks that 100% technically equivalent to their counterparts, and run complex mock behavior that relates to assessing unexpected errors, long response times, or invalidities.
In summary, the mocking stage is an invaluable time for developers to work out mistakes, get the processes right, and be on track for a fully working virtualization of the API.