If a smoke test becomes flaky, investigate right away. These are your release gatekeepers - if they’re unreliable, confidence in your entire build pipeline drops.
Start by reviewing environment stability and timing dependencies. Even a small infrastructure glitch can create big reliability gaps at that level. Smoke tests should be your most predictable suite.
AI testing platforms like LambdaTest make it easier to manage flakiness by allowing automatic retries, clear logging, and integration into dashboards.
The trick is to log every retry distinctly so patterns don’t get buried. When you can see retry trends over time, it’s much easier to spot which tests or environments are repeatedly failing.
Flakiness heatmaps and historical failure charts are fantastic for visualization. They make it obvious where instability clusters - by test suite, environment, or release version.
Comparing CI results to local runs helps narrow down whether it’s the infrastructure or the test itself. Use that insight to prioritize the highest-impact fixes first.
AI can now auto-repair locators or adjust test flows dynamically, which is great for fast-moving UIs.
But I always recommend a human review before merging those changes. Sometimes AI might adapt a test in a way that hides a real bug. Use AI to save time, not to replace judgment. Validation still needs human eyes.
To reduce brittle tests, focus on using robust locators, dynamic element handling, and parameterized waits.
CSS and XPath locators tied to layout elements are fragile - prefer IDs or accessible attributes. AI-assisted handling can fill in the gaps, especially when the DOM changes frequently. The goal is resilience, not just automation.
When testing in cloud or distributed setups like Kubernetes, flakiness often stems from scheduling delays, network latency, or inconsistent database states.
Even caching behavior or parallel test execution can cause odd timing mismatches. The fix is isolation - clean containers, controlled data, and health metrics to catch degradation early. Retries are fine as a safety net, but never a crutch.