You run a test, detect a failure, analyze the issue, and then find out that the same test passed in the next execution under the same conditions. This is especially frustrating in large CI/CD test suites.
You might be wasting time fixing failures that aren’t caused by real defects, which directly impacts team productivity and slows release cycles.
If you’re experiencing high test flakiness in automated pipelines, this blog will help you address the issue. We’ll cover causes of flaky tests, reliable detection methods, and management strategies.
Improve test stability, reduce maintenance effort, and accelerate CI/CD releases with TestGrid.
What Is a Flaky Test?
Flaky tests are automated tests that pass in one run and fail in another without any changes to the app code, the test code, or the test configuration. These tests can result from unstable test environments or external dependencies.
Flaky tests can behave unpredictably and produce non-deterministic results across executions, which is why they’re hard to reproduce and diagnose. This can reduce the overall reliability of your automated test suites and software quality.
How Do Flaky Tests Affect Your QA Workflows?
1. Lower confidence in automation reports
When your test failures don’t consistently indicate actual defects, your QA team can’t fully trust the test results. They have to spend additional time investigating whether the failures happened because there’s an issue in the code or from an unstable test case.
2. Slower CI/CD pipelines and delay in releases
Flaky tests can slow down your CI/CD pipelines by causing builds to fail unexpectedly. Your app code could be functioning correctly, but false negatives caused by flaky tests can force your teams to rerun tests, examine failures, and validate results before they can even proceed with deployments. These extra verification steps increase your execution time.
3. Negative impact on regression and smoke tests
Smoke and regression tests help you quickly check the functionality of your app after you make code changes or before releases. If your test suites have flaky tests, they may create false alarms and make your team believe a new build is faulty even if it’s not. Unreliable regression and smoke test results can block your release pipelines.
4. Higher maintenance
Fixing flaky tests requires frequent updates, refactoring, and monitoring. You may have to adjust update locators, improve test data management, or address environment issues to keep your tests stable. This can take up a significant portion of your time and move your focus away from core QA tasks.
Common Causes of Flaky Tests
There’s no one single cause of flaky tests. There could be issues within your test framework, scripts, frameworks, or the supporting test infrastructure.
These are some of the most common reasons that can create test flakiness:
Effective Strategies to Detect Flaky Tests
You now know what flaky tests are. The next step is to learn the methods that can help you spot them.
1. Run repeated test executions
Run the same test repeatedly under the same conditions and compare the results.
Say, for example, when you execute a login test 20 times under the same test environment, credentials, and app build, it should ideally pass all 20 runs. But if it passes 17 times and fails 3 times without any code changes, it indicates that the test may be flaky.
You can implement automated reruns in your CI/CD pipeline to speed up the process and troubleshoot non-deterministic tests faster.
2. Analyze logs, screenshots, and recordings
You should assess execution logs, screenshots, and session recordings from both your failed and successful runs. The comparison between these test artifacts will help you detect app behavior, timing, test data, or environment conditions that are causing the intermittent failures.
- Look for inconsistent error messages that show up only in certain executions
- Compare execution timestamps to spot delays, timeouts, or slow-loading components
- Check if the elements were unavailable, hidden, or not fully loaded when interactions happened
- Review the screenshots for unexpected pop-ups, overlays, or notifications
- Compare your browser, device, network, and environment configs across passing and failing runs
3. Use automated flaky test detection tools
A Bitrise report shows that dev teams who invest in monitoring tools encounter 25% fewer flaky reruns and higher build success rates. When your test suites grow, manually identifying flaky tests can get tough.
These tools can help you simplify the process:
Test management and reporting tools allow you to assess historical test results and spot tests with inconsistent execution outcomes
Browser automation frameworks like Playwright can help you collect traces, screenshots, videos, and execution logs for identifying false failures
Connecting with CI/CD tools such as Jenkins, GitHub Actions, and GitLab CI enables you to configure automated test reruns and compare results across multiple executions
Test observability platforms like Datadog CI Visibility let you track your flaky test rates, execution trends, and recurring failure patterns
Managing Flaky Tests in CI/CD
1. Replace static waits with explicit waits
Static waits pause your execution for a fixed duration regardless of whether the required condition is met, which can make your tests sensitive to network latency, server load, and CI environment performance.
You should rather apply explicit waits, which stop execution only until a specific element state, API response, or app condition is satisfied, and improve test reliability.
2. Isolate tests and remove shared state
Since shared databases, user accounts, files, or environment settings can create unintended dependencies that cause test failures, you must design tests that can execute independently without relying on data, configurations, or artifacts created by other tests.
For that, you can create dedicated test data, reset app state between executions, and ensure each test performs its own setup and cleanup.
3. Apply shift-left testing for early detection
Run your tests during local development, pre-merge checks, and pull requests. This will help you find synchronization issues and unstable assertions before they reach your CI environments. This also allows you to easily trace failures back to recent code changes and reduce the time spent on root cause analysis and troubleshooting.
4. Improve locator strategies for stability
Stable and unique locators are generally more reliable than dynamic IDs, element positions, or complex XPath expressions, which can become invalid after layout updates.
Therefore, use dedicated test attributes, stable IDs, or accessibility attributes, and review locators regularly to ensure they remain resilient as your app changes.
Flaky Test Examples Across Frameworks
Flaky tests can happen in any automation framework. But the underlying causes might vary depending on how the framework handles browser interactions, synchronization, network requests, and test execution.
Best Practices to Reduce Flaky Tests in Test Automation
1. Configure automatic test retries
Automatic retries help you identify intermittent failures that are caused by transient issues such as temporary network disruptions, infrastructure glitches, or short-lived service unavailability. Make sure you track retry occurrences to distinguish real defects from unstable test behavior.
Pro tip
Don’t assess your test stability based only on final pass rates. You should monitor metrics like retry frequency and retry success rates, and look for increasing retry counts, as this can indicate your tests are unstable and relying on reruns to pass.
2. Maintain clean test data
You need to implement processes which help you keep your test data accurate, consistent, and aligned with your current app state. Outdated, corrupted, or unrealistic datasets can generate misleading test outcomes and make it hard for you to diagnose and reproduce failures.
Pro tip
Check your test data regularly, remove obsolete records, and ensure that your datasets reflect real-world usage scenarios. You can also version-control your test data to track data changes and quickly identify if a failure is related to a recent data modification.
3. Make test stability a shared quality goal
Flaky tests can occur because of changes in app behavior, infrastructure, test frameworks, or deployment environments. And these factors are not controlled by a single team. That’s why you need to make test stability a shared responsibility among your development, QA, and DevOps teams.
Pro tip
Establish clear ownership for investing and resolving flaky tests. Define stability metrics (e.g., flaky test rate, false failure rate, quarantine test count) and track them in periodic quality reviews.
4. Design tests for determinism
Tests that depend on the current system time or specific execution timings can become unstable if dates, time zones, processing speeds, or response times vary across your test environments. This is why you must design tests with predictable inputs and controlled dependencies.
Pro tip
You can reduce the sources of unpredictability by mocking random number generators, fixing timestamps, and using consistent test configurations. This will make it easy for you to reproduce test outcomes and resolve flaky tests.
Using TestGrid to Reduce Flaky Tests and Improve Reliability
For your team to efficiently detect flaky tests, they need stable automation, better visibility into test executions, and reliable test-monitoring mechanisms to track test stability.
TestGrid is a unified, AI-powered testing platform that lets you automate your web and mobile tests faster with low-code, no-code, and record-and-playback capabilities.
The platform’s AutoHeal technology repairs your broken tests by identifying new locators and objects. This helps you prevent unnecessary test failures and reduce the maintenance effort.
TestGrid provides detailed execution insights, logs, screenshots, and reporting capabilities so your team can analyze failures more efficiently and detect recurring flakiness patterns.
Moreover, the platform offers support to automation frameworks like Selenium, Appium, and Cypress. This enables you to build and manage deterministic test suites in your chosen framework and scale execution across CI/CD pipelines.
Build resilient testing workflows with AI automation, intelligent reporting, and enterprise-grade execution capabilities using TestGrid.
This blog is originally published at TestGrid
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