Why this matters
Flaky tests waste time, hide real regressions and encourage rerunning pipelines until they turn green. The damage is not only technical; it changes team behaviour and weakens trust in the whole suite.
Flakiness must be treated as a defect with ownership, evidence and prevention—not as an unavoidable property of automation.
How to do it well
Detect and quantify
Track repeated outcomes for the same commit and identify tests with unstable results.
Capture evidence
Store traces, screenshots, network calls, console output and timing information on every failure.
Classify the cause
Separate product race conditions, test-data conflicts, environment issues and weak synchronisation.
Quarantine transparently
Keep unstable tests from blocking releases only with an owner, ticket and deadline.
Fix the design
Use observable waits, independent data, controlled clocks and deterministic dependencies.
Prevent recurrence
Review new tests for isolation and monitor suite reliability as a first-class metric.
What to avoid
- Adding retries until failures disappear.
- Using fixed sleep durations for asynchronous behaviour.
- Sharing accounts or records across parallel tests.
- Leaving quarantined tests indefinitely.
- Blaming infrastructure before collecting evidence.
Practical example
A UI test fails because a save notification appears after a variable delay. Replacing a two-second sleep with a wait for the confirmed API response removes timing dependence.
A second test becomes stable only after each run creates its own unique audience instead of reusing one shared record.
Lesson for practice
Flaky tests are a quality problem in the test system. Fast diagnosis, isolation and visible ownership protect the credibility that makes automation useful.
A good practice does not have to be complicated. It should be intentional, repeatable and explainable: the team should understand why the control exists, what evidence it provides and how feedback will improve the next iteration.