Taming Flaky Tests with Docker Containers
Flaky tests can be a major headache for developers, causing frustration and wasting time. These tests produce different results on different runs, even when the code and inputs remain the same. In this article, we’ll explore how to use Docker containers to beat flaky tests and ensure reliable testing.
The Problem with Flaky Tests
Flaky tests compromise software integrity and slow down development velocity. They can be caused by various factors, including randomness, race conditions, or dependencies on external services. When tests are non-deterministic, it’s challenging to identify the root cause of failures.
Why Use Docker Containers?
Docker containers provide a consistent and isolated environment for testing, eliminating the variability that leads to flaky tests. By using containers, we can:
- Isolate the application’s runtime environment from the host operating system
- Minimize shared resource usage
- Ensure tests are properly isolated
Testing a Node.js Application
Let’s test an Express.js-powered Node.js app that stores and reads job listings. We’ll use Postgres for persistence and Knex.js for managing migrations and seeds.
Setting Up the Test Environment
We’ll create a Dockerfile and a docker-compose.yml manifest to define our test environment. Our Dockerfile will include instructions for building our application image, while the docker-compose.yml file will define two services: the simple-job-board service and the db service.
Running Tests in Docker Containers
With our test environment set up, we can run our tests using docker-compose run test. This ensures that our database service spins up before our tests start running. Our test results will pass with green checkmarks, indicating that our tests are running reliably in the Docker containers.
Reducing Flakiness
By using Docker containers and test isolation, we’ve greatly reduced the chances of encountering flaky tests. We’ve created new connections and spun up new databases for each test run, guaranteeing a clean slate for each run. We’ve also eliminated state contamination as a source of flakiness.
Conclusion
In this article, we’ve demonstrated how to use Docker containers to beat flaky tests. By providing a consistent and isolated environment for testing, Docker containers help ensure reliable testing. Remember that test flakiness is multi-variate in nature, and there are other sources of flakiness, such as async behavior, concurrency issues, and network interactions.