How to write integration tests for distributed systems?

Summary

In this video, the speaker explores how to write stable integration tests for distributed systems and avoid flakiness. Key points include identifying the causes of flaky tests, such as environmental issues and poor architecture, and using contract-based testing to ensure consistent APIs between clients and providers. For smaller systems, Docker Compose can simulate environments locally, while larger systems benefit from minimal smoke tests. The speaker advises maintaining a small, efficient set of tests to cover core functionality and emphasizes the importance of the testing pyramid in achieving stable and scalable testing practices.

Takeaways

• 😀 Avoid running integration tests directly in live environments due to challenges with state consistency and flaky results.
• 😀 Contract-based testing is a key strategy for ensuring stable integration tests in distributed systems by validating API contracts between clients and service providers.
• 😀 Using tools like Pact can help clients and service providers ensure that the API specification remains consistent, reducing the risk of unexpected failures.
• 😀 It's essential for service owners to provide client libraries based on API specifications, ensuring that dependencies are always up to date and correctly implemented.
• 😀 For smaller distributed systems, using tools like Docker Compose to run services locally can mimic a production-like environment for integration testing.
• 😀 The more integration tests you have, the higher the likelihood of flaky tests due to network issues or intermittent failures. Keep your integration tests minimal and focused.
• 😀 Apply the testing pyramid concept: prioritize unit tests, with a smaller focus on integration tests, and only a few critical end-to-end tests at the top of the pyramid.
• 😀 Smoke tests should be run regularly on core system functionality in production or QA environments to ensure critical flows are working as expected.
• 😀 Stubbing and mocking third-party services should only be used as a last resort, as they can quickly become outdated or high-maintenance, leading to inaccurate test results.
• 😀 Local integration testing with Docker Compose or similar tools can help simulate a production-like environment for mid-sized distributed systems, ensuring more reliable tests.

Q & A

What is the main issue with flaky integration tests in distributed systems?

The main issue with flaky integration tests arises when they are run in live environments without proper isolation. This leads to inconsistencies between different services, network issues, and unmanageable states that cause tests to fail unpredictably.

Why is it not recommended to run integration tests in live environments?

Running integration tests in live environments is risky because you could create unpredictable states and inconsistencies across services, which can lead to flaky tests. It's difficult to ensure that all services are in a consistent state when tests are executed.

What is contract-based testing, and why is it useful?

Contract-based testing is a method where the expectations between a client and service provider are verified to ensure they are consistent. It is useful because it allows you to focus on the API contract between services, reducing the risk of flaky tests caused by mismatched expectations.

What are the benefits of using contract-based testing over traditional integration tests?

Contract-based testing ensures stability by focusing on verifying that service providers adhere to agreed-upon API specifications. This reduces the need for running full integration tests on live systems, avoiding flaky tests due to unexpected changes or network issues.

How does Docker Compose help in testing smaller distributed systems?

Docker Compose allows you to containerize all your services and run them locally in a controlled environment. This makes it easy to simulate production conditions and run integration tests on smaller distributed systems without needing to rely on live environments.

Why might it be impractical to run tests for larger distributed systems locally?

For larger distributed systems, it's often impractical to run tests locally because the number of services and third-party dependencies makes it difficult to replicate a production-like environment on your local machine.

What is the recommended approach for testing large systems with third-party dependencies?

For large systems, it's recommended to use contract-based testing or smoke tests. These tests focus on ensuring critical functionality works without running full integration tests, which can be unstable due to third-party dependencies or the complexity of the system.

What is the testing pyramid, and how does it help avoid flaky tests?

The testing pyramid suggests that most testing should occur at the lower levels (unit and contract tests), with fewer tests at the higher levels (integration and end-to-end tests). By applying this approach, you limit the number of complex, flaky integration tests and focus on the most critical paths.

How can mocking and stubbing be used in integration tests, and what are their potential pitfalls?

Mocking and stubbing can simulate external services in integration tests, especially for critical third-party systems. However, they can become outdated if the mocked service changes, leading to tests that no longer reflect the real-world behavior of the service, which can result in inaccurate test results.

What should be the focus of smoke tests in integration testing?

Smoke tests should focus on ensuring that the most critical functionality of the system works end-to-end. These tests are usually run on a small set of critical paths and are meant to quickly identify any major issues with the system, without the complexity of full integration tests.