Fixing Test Timeouts: A Guide To Faster CI Performance

In the fast-paced world of software development, test performance is not just a metric; it's a lifeline. When tests time out, especially in Continuous Integration (CI) environments, it throws a wrench into the entire quality improvement process. For projects like our legal tech app, where vulnerable users rely on the software's correct functioning, reliable tests are absolutely critical. This article dives into a recent case where tests were timing out after 20 minutes, blocking crucial quality enhancements. We'll explore the root causes, the steps taken to address them, and the ultimate goal of achieving a test suite that completes in under 2 minutes. Let’s embark on this journey to optimize test performance and ensure our application remains robust and dependable.

The Problem: 20-Minute Test Timeouts

Our CI workflow had hit a major roadblock: tests were timing out after a frustrating 20 minutes. This wasn't just an inconvenience; it was a critical issue that prevented any further quality improvements. Imagine trying to debug a complex system when your tools are constantly failing – that’s the situation we were in. Further compounding the issue, local tests, which should provide quick feedback, were taking an agonizing 11+ seconds for just 1743 tests. This sluggish performance highlighted a deeper problem within our testing infrastructure. The biggest offender? Full database migrations were running for every test file, a process repeated 19 times across numerous files. The result was a test suite that was, frankly, unusable in its current state. To truly understand the magnitude of the problem, let’s delve deeper into the root causes that contributed to these timeouts.

Root Causes: Unraveling the Mystery

To effectively tackle the test timeout issue, we needed to identify the underlying culprits. After careful analysis, four key root causes emerged:

1. Heavy Test Setup: The most significant bottleneck was the way our tests were set up. Each test file was initializing a full database, complete with migrations. This meant that for every test file, the entire database schema was being recreated from scratch, a process that is inherently time-consuming. Think of it as building a house from the ground up for every single inspection – highly inefficient!
2. No Test Database Reuse: Adding to the inefficiency, we weren’t reusing the test database across tests. Instead of creating a single, persistent database instance for the entire test suite, each test file was getting its own isolated database. This meant redundant work, as the same migrations were being executed repeatedly.
3. Sequential Execution: By default, our test runner (Vitest) was running tests sequentially. This meant that tests were executed one after another, without leveraging the potential of parallel processing. In a world of multi-core processors, running tests sequentially is akin to using a single lane on a multi-lane highway – a massive waste of resources.
4. Heavy Service Mocking: Our tests were also weighed down by heavy service mocking. Services like encryption and authentication, along with the full application stack, were being initialized for each test. While mocking is essential for isolating units of code, excessive mocking can lead to performance bottlenecks. It’s like preparing an elaborate meal for every taste test, even if you only need a small sample.

Understanding these root causes was the first crucial step in our journey to reclaim test performance. With a clear picture of the problem, we could now define our requirements and strategize our approach to solving it.

Requirements: Setting the Stage for Success

Our primary target was clear: tests must complete in under 2 minutes in CI. This wasn't just a nice-to-have; it was a critical requirement for unblocking quality improvements and ensuring the reliability of our legal tech app. To achieve this ambitious goal, we outlined a phased approach, focusing on quick wins followed by more architectural changes. This allowed us to make immediate progress while laying the foundation for long-term test performance.

Phase 1: Quick Wins

In Phase 1, we focused on low-hanging fruit – changes that could be implemented quickly and yield immediate results. This phase comprised three key objectives:

1. Configure Vitest for Parallel Execution: Vitest, our test runner, has the capability to run tests in parallel. However, by default, it operates sequentially. The first quick win was to configure Vitest to leverage parallel processing, allowing tests to run concurrently and significantly reduce overall execution time. This is akin to opening up multiple lanes on our test execution highway.
2. Optimize Test Database Setup: We aimed to optimize test database setup by reusing an in-memory database across tests. Instead of creating a new database for each test file, we would create a single in-memory database instance and share it across the entire test suite. This drastically reduces the overhead of running migrations repeatedly. Think of it as having a shared kitchen instead of setting up a new one for every meal.
3. Mock Heavy Services in Unit Tests: To further lighten the load on our tests, we decided to mock heavy services, such as encryption and AI calls, specifically in unit tests. This meant isolating the units of code being tested and avoiding the overhead of initializing entire services for each test. It’s like focusing on the taste of a single ingredient rather than preparing the whole dish.

Phase 2: Architecture

Phase 2 shifted our focus to more architectural changes, aimed at achieving sustainable test performance and maintainability. This phase included the following objectives:

1. Separate Unit Tests from Integration Tests: A key architectural improvement was to separate unit tests from integration tests. Unit tests focus on individual components in isolation, while integration tests verify the interaction between different parts of the system. Separating these types of tests allows for more targeted and efficient testing. It’s like having dedicated workshops for different aspects of a project, rather than trying to do everything in one space.
2. Use Test Database Fixtures: Instead of running full database migrations for each test, we planned to implement test database fixtures. Fixtures are pre-populated database states that can be reused across tests, eliminating the need for repeated migrations. This significantly reduces test setup time and makes tests more predictable. Think of it as using pre-assembled building blocks instead of constructing each one from scratch.
3. Implement Proper Test Isolation: Finally, we aimed to implement proper test isolation without full reinitialization. This meant ensuring that tests don’t interfere with each other’s state, without the overhead of completely resetting the environment for each test. It’s like having designated workspaces that don’t get cluttered by neighboring projects.

By outlining these phases and objectives, we set a clear roadmap for tackling the test timeout issue and improving overall test performance.

Success Criteria: Measuring Our Progress

To ensure our efforts were effective, we established clear success criteria. These criteria weren't just about speed; they were also about maintaining test quality and reliability. Our success would be measured against the following:

• ✅ All tests complete in under 2 minutes in CI: This was the primary goal – to bring our test suite execution time within the 2-minute threshold in the CI environment. This would unblock quality improvements and ensure timely feedback on code changes.
• ✅ Tests still pass (or reveal real failures, not timeouts): It was crucial that our optimizations didn't mask real issues in the code. Tests should still pass if the code is correct, and they should fail only when there are genuine problems. Timeouts, in this context, are not valid failures.
• ✅ Test quality maintained or improved: Ultimately, our goal was to not only speed up tests but also to maintain or improve their quality. This meant ensuring that tests were comprehensive, reliable, and provided valuable feedback on the application's behavior.

With these success criteria in place, we had a clear benchmark for evaluating the effectiveness of our interventions. Now, let’s consider the broader context of this issue and why it was so critical for our legal tech app.

Context: Why This Matters

Our legal tech app serves vulnerable users, making the reliability of our software absolutely paramount. People's cases and well-being depend on this application working correctly. In this context, test timeouts weren't just a technical inconvenience; they were a potential threat to the very users we aimed to serve. We can't address the 61 test failures if tests timeout before finishing. This is akin to trying to fix a car while the engine keeps shutting off – an impossible task.

Reliable tests are the bedrock of a robust software system, especially in critical applications like ours. They provide the confidence that the software behaves as expected and that changes don't introduce unintended consequences. When tests timeout, this confidence erodes, and the risk of releasing flawed software increases dramatically.

Therefore, fixing the test timeout issue was not just about improving performance; it was about upholding our commitment to providing a reliable and trustworthy application for vulnerable users. It was about ensuring that justice is served, not delayed by technical glitches. With this understanding, let's proceed to a conclusion.

Conclusion

Addressing test performance issues, especially timeouts in CI, is crucial for maintaining software quality and reliability. In our case, where a legal tech app serves vulnerable users, the urgency was even greater. By systematically identifying root causes, setting clear requirements, and implementing a phased approach, we aimed to bring our test suite under the 2-minute threshold while ensuring test quality. The journey involved quick wins like parallel test execution and database reuse, as well as architectural changes like separating unit and integration tests and using database fixtures.

The success criteria focused not only on speed but also on maintaining test accuracy and overall quality. This comprehensive approach underscores the importance of reliable tests in building trustworthy software, especially when people's well-being is at stake.

For further reading on test optimization strategies, check out this comprehensive guide on software testing.