Developer’s machine > dev shared environment > staging environment > UAT > production.
Probably not exactly how everyone structures their delivery pipelines but probably not that far off. It allows instant feedback on whether what a developer is writing actually works with the code other developers are writing. And that’s a really good thing. Unfortunately, it misses something…
Each environment (other than the developer’s own machine) is shared with other developers who are also deploying new code at the same time. So how do you get an integration test for component A that relies on component B behaving in a custom manner (maybe even failing) to run automatically, without impacting the people who are trying to build and deploy component B?
If we were writing a unit test we would simply inject a mocked dependency. Fortunately there’s now a fantastic piece of kit available for doing exactly this but on an integration scale: enter Mountebank.
This clever piece of kit will intercept a network call for ANY protocol and respond in the way you ask it to. Transparent to your component and as easy to use as most mocking frameworks. I won’t go into detail about how to configure ‘Imposters’ as their own documentation is excellent, but suffice to say it can be easily configured in a TestFixtureSetup or similar.
So where does this fit into our pipeline? Personally, I think the flow should be:
Push code to repo > Code is pulled onto a build server > Build > Unit test > Integration test > Start deployment pipeline
The step where Mountebank comes in is obviously ‘integration testing’.
Keep in mind that installing the component and running it on the build agent is probably not a great idea, so make good use of the cloud or docker or both to spin up a temporary instance which has Mountebank already installed and running. Push your component to it, and run your integration tests. Once your tests have run then the instance can be blown away (or if constantly destroying environments gets a bit slow, maybe have them refreshing every night so they don’t get cluttered). Docker will definitely help keeping these processes efficient.
This principle of spinning up an isolated test instance can work in all kinds of situations, not just where Mountebank would be used. Calls to SQL Server can be redirected to a .mdf file for data dependent testing. Or DynamoDb tables can be generated specifically scoped to the running test.
What we end up with is the ability to test more behaviours than we can do in a shared environment where other people are trying to run their tests at the same time. Without this, our integration tests can get restricted to only very basic ‘check they talk to each other’ style tests which although have value do not cover everything we’d like.
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