Flaky Tests in 2026: How to Identify, Fix, and Prevent Them
In 2026, flaky tests aren’t just an annoyance; they’re a blocker for modern CI/CD. For software teams, nothing is more frustrating than tests that fail inconsistently. They waste time, obscure real issues, and break trust in automation.
Flakiness doesn’t just slow you down; it leads to confusion, endless debugging, and false positives/negatives that no one has the patience to chase down. The real cost? Wasted cycles and a slow-moving pipeline, ultimately blocking the path to fast, reliable releases.
Here’s the thing: flaky tests undermine everything CI/CD stands for. Let’s break down how they happen, why they matter, and how you can fix them.
What Is a Flaky Test?
A flaky test is one that fails intermittently without any change in the code. Put simply, these tests can succeed one time, fail the next, succeed again, even though there has been no change by the application code at all.
Flakiness testing = inconsistent results. A common example is a login test that sometimes passes, sometimes fails, without any underlying changes in the login code. The unpredictable nature of flaky tests creates an environment where you can’t rely on the test results, and that’s a big problem for CI/CD pipelines.
Also Read: Managing Flaky Tests with AI: RCA at Scale
Why Tests Become Flaky?
Now, let’s get into the issue. Why do flaky tests even happen? Here are the main culprits:
1. Test Environment Issues
Unstable infrastructure, network latency, or problems with environments like staging and production can cause tests to fail unpredictably. Without a solid, stable testing environment, even perfectly written tests can become flaky test cases.
2. Data Dependency
Flaky behaviour can occur if the test data is not properly reset or reused. Consider a scenario where you are executing a test for which certain data is supposed to exist in a specific state. Improper cleaning of the data can also provide variable results for every test run.
3. Timing/Synchronization
Tests could start failing intermittently just because of race conditions or incorrect waits (like waiting for a UI element that is not yet fully loaded). You would likely face these challenges when your tests run in parallel or are asynchronous, as more modern apps these days tend to be.
4. Third-Party Dependencies
External APIs, third-party services, or sandbox environments tend to be flaky. Your side may be working perfectly fine, but an API outage or a third-party service limit can render a test as failed.
5. UI Brittleness
UI elements are constantly changing in dynamic applications. If the locators are brittle or the elements change frequently, UI tests will break, leading to flaky UI tests. This is particularly common in flaky test cases, which can be easily affected by minor changes in the front-end code.
6. Concurrency Issues
Tests that aren’t designed for parallel runs can clash with each other, causing failures in some cases but not others. These concurrency issues can arise when different tests are interacting with the same resources simultaneously.
These are just a few of the causes of flaky tests, but each one of these has a clear solution. Understanding them is the first step in fixing the problem.
Why Flakiness Hurts CI/CD Pipelines?
Flaky tests cause more than just frustration; they actively slow down your CI/CD pipeline. Here’s how:
- Slows Down Releases: If tests fail intermittently, releases are delayed as teams investigate failures that aren’t actually issues.
- Blocks Automated Pipelines: When flaky tests in CI/CD cause red builds, pipelines get stuck. This leads to wasted time and resources, and developers can’t trust the automated testing process.
- Reduces Developer Trust in QA Results: If tests fail without clear reasons, developers will lose trust in QA results. This makes them less likely to rely on the automated testing process at all.
- Inflates Maintenance Costs: Investigating flaky test automation issues takes up time that could be better spent addressing real issues or improving test coverage.
Identifying Flaky Tests Early
You can’t fix flaky tests if you don’t know where they are. Here are some ways to identify flaky tests early in your pipeline:
- Tracking Failure Types on Dashboards: Where we can track recurring test failures and tests that have a history of flakiness on a dashboard.
- Reruns/Retries to validate Failures: For the tests that fail randomly, retry them to check if the failure is actual or flaky.
- Flagging Tests with Unstable Histories: flag tests that are intermittent failures, especially those that have had a number of failures without a code change.
- Observing Execution Logs: Go through test execution logs and look for clues in order to identify timing problem or environmental instability.
How do you Handle Flaky Tests in your Automation Suite: Practical Fixes
So, here are a few actionable steps you can take to minimize flaky tests and make your automation suite more reliable:
1. Environment Stabilization
Use mocks and containerization for stabilization of the environment. Minimize flaky tests related to external dependencies by building reproducible test environments. Containerization guarantees your tests remain unaffected by inconsistencies in the local machine, thereby ensuring similar behavior across various environments. Mocks are useful to mimic the behavior of third-party services, so when an issue does occur with the external systems, it will not affect your tests.
2. Optimize Waits/Sync
A key area to focus on when writing automation tests for dynamic applications is the use of waits/Sync. For example, instead of waiting for an element like this: just waiting, waiting, waiting for the element to appear, poll regularly and test for availability. This way, there will be no race conditions and the test is guaranteed to have whatever resources it needs before being invoked.
3. Data Strategy
Stale or inconsistent data is a major cause of flaky tests. Always reset your test data between runs to ensure every test starts with the same baseline. This prevents data conflicts from influencing test results. Additionally, consider using fresh datasets or seed resets to avoid unintended dependencies.
4. Smarter Retries
Implement smarter retries that don’t loop endlessly but are limited to a few attempts. This avoids the issue of stuck pipelines and ensures tests only rerun when needed. Endless retries can create a false sense of security, masking real issues.
5. Isolation for Parallel Runs
When running tests in parallel, ensure that each test has isolated resources to work with. Shared resources can cause concurrency issues that lead to flaky test detection failures. Proper isolation helps maintain consistency in parallel test executions.
Real-World Flaky Test Examples:
Imagine a retail company that struggled with flaky UI tests due to dynamic elements on their website. After implementing explicit waits and using mock services for payment gateway interactions, the frequency of flaky tests dropped significantly. Additionally, they isolated test environments using Docker containers, ensuring consistency across different stages of testing. This combination of practices resulted in a 70% reduction in flaky failures and improved their overall release confidence.
The Future of Flaky Test Management in 2026
As AI continues to advance, the future of flaky test management looks promising. Tools like ACCELQ are already working to make it easier to handle flaky tests with AI-driven test orchestration. Here’s what the future holds:
- Automatic Prediction of Randomized Tests Likely to be Flaky by AI/LLMs: Machine learning algorithms will predict which tests are likely to turn flaky, helping QA teams address the issues beforehand.
- Self-Healing Locators Make UI Brittleness a Thing of the Past: New tools that will mend the locator failure automatically and help in reducing the flakiness of UI.
- Predictive Test Selection: AI would predict the tests that are most likely to fail, thereby optimizing testing cycles and minimizing flakiness. CI/CD pipelines would deal less with flaky tests.
Conclusion
You lose confidence in your automation when your tests are flaky. The first step in addressing flakiness is to identify what is causing the flakiness, which can allow your pipeline to get on track. QA teams can regain the reliability of automation and prevent flakiness testing from becoming a bottleneck through smarter tooling and practices built for 2026, such as ACCELQ’s AI-driven Autopilot test orchestration.
Balbodh Jha
Associate Director Product Engineering
Balbodh is a passionate enthusiast of Test Automation, constantly seeking opportunities to tackle real-world challenges in this field. He possesses an insatiable curiosity for engaging in discussions on testing-related topics and crafting solutions to address them. He has a wealth of experience in establishing Test Centers of Excellence (TCoE) for a diverse range of clients he has collaborated with.
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