Playwright tests pass once, then rage-quit over duplicate rosters: 5 ways to stop your automation suite from self-destructing

Test automation engineers often encounter issues with test data management, particularly when running multiple tests in parallel. A common problem is that a test may fail due to existing data, such as a roster with the same name already existing. To address this, five patterns for handling test data in Playwright have been identified, ranging from simplest to most robust. These include deleting created data after each test, generating unique identifiers for every test execution, using API cleanup, wrapping tests in database transactions, and creating dedicated test environments with pre-seeded data pools. According to TestDino Insights, the most reliable pattern for parallel execution and CI/CD pipelines is generating unique identifiers for every test execution. Additionally, investing in execution visibility is crucial to debugging and saving time. TestDino's platform provides automatic tracking of test inputs, execution context, and failure patterns, helping teams running Playwright at scale to distinguish between data collisions and actual bugs.