Flaky Tests Explained: Why Your Tests Keep Failing

Flaky tests are tests that fail unpredictably — passing one moment and failing the next without meaningful code changes. They are one of the most common and costly problems in automated testing.

This page explains why flaky tests happen, how they emerge in CI/CD environments, and which patterns repeatedly lead to unreliable test behavior.

Start with the FAQ Lessons learned
Testing CI/CD Automation Quality
What this page focuses on

Structural causes of flakiness, recurring failure patterns, and systemic issues in automated test environments.

What this page avoids

Framework hype, tool-specific tutorials, and superficial fixes that hide deeper problems.

Why this matters

Reliable tests are foundational to confident deployments. Flaky tests undermine trust, slow teams down, and increase operational risk.

Why tests become flaky

Timing & async behavior

Race conditions, sleeps, retries, and assumptions about execution order frequently cause nondeterministic failures.

Shared state

Tests that rely on shared databases, caches, or external services can interfere with one another in unpredictable ways.

Environment drift

Differences between local machines, CI runners, and production-like environments often expose hidden assumptions.

Lessons learned from flaky test suites

Teams struggling with flaky tests often discover that the root causes are not isolated bugs. Flakiness usually points to deeper issues in system design, test boundaries, or assumptions about determinism.

Over time, flaky tests condition teams to distrust failures, rerun pipelines, or disable tests entirely — weakening the feedback loop testing is meant to provide.

Reducing flakiness requires treating tests as first-class system components, designed with the same care as production code.

Frequently Asked Questions

A test becomes flaky when its outcome depends on timing, execution order, shared state, or external conditions rather than purely on deterministic logic.

CI environments introduce parallel execution, variable performance, and constrained resources that expose weaknesses not visible locally.

Often yes. Flaky tests commonly indicate unclear boundaries, over-coupling to system internals, or assumptions about execution timing.

Retries may reduce noise temporarily but often hide the underlying causes, allowing flakiness to persist and grow unnoticed.

While some nondeterminism is unavoidable, most flakiness can be significantly reduced through better isolation, clearer contracts, and more deterministic system design.