Testing
Retrying failing tests is a controversial topic. Critics say it hides flakiness and trains developers to ignore failures. Proponents say some level of retry is pragmatic in distributed test environments. Both are right — the answer is about when and how you retry. The Case Against Retries Automatic retries mask flaky
Testing
You've identified a flaky test. You can't fix it right now — it's intermittent, the root cause isn't clear, and you have a release to ship. What do you do? Deleting the test loses coverage. Skipping it silently means the failure is invisible.
Testing
A test suite developers trust is worth more than a large test suite developers ignore. Reliability — tests that pass when code is correct and fail when it isn't — is the foundational property. Everything else is secondary. This guide covers how to build that reliability from the start, and
Testing
"It works on my machine" is one of the oldest complaints in software development. With tests, the equivalent is "it passes locally but fails in CI." This pattern has specific, identifiable causes — and fixing them systematically makes your test suite dramatically more reliable. Why CI Is
Testing
Flaky tests are tests that pass sometimes and fail sometimes without any code changes. They're among the most damaging problems in a test suite — they erode trust in the entire test suite, slow down CI pipelines, and hide real failures behind noise. If your team regularly reruns tests
Test Reliability
Flaky tests cost CI time and erode confidence. Playwright gives you several tools to manage flakiness: automatic retries that reduce false negatives, --repeat-each for detecting flakiness before it hits CI, and test.fail() for acknowledging known issues without deleting coverage. This post covers all three strategies — when to use
Test Reliability
When a flaky test blocks your CI pipeline, you have three bad options: delete it (lose the coverage), skip it (test.skip, forget it forever), or fix it immediately (takes time you don't have). The quarantine pattern is the fourth option: isolate it, run it separately, and track
Test Reliability
A flaky test is a test that passes sometimes and fails sometimes without any change to the code. It fails in CI, you re-run it, it passes. You ship. Three days later it fails again. Nobody changed anything relevant. Flaky tests are expensive. They erode trust in your test
Test Reliability
Production services have SLOs — "99.9% of requests succeed within 500ms." Test suites have... hope. Engineers hope their tests are stable, hope failures mean real bugs, hope the suite is trustworthy. When tests fail, they re-run and hope. This informal relationship with reliability is the source of
Test Reliability
Flaky tests are hard to detect manually — a test that fails 5% of the time looks like noise until someone tracks it across 20 CI runs. GitHub Actions gives you tools to surface flaky tests automatically: test annotations that appear directly on pull requests, workflow features for re-running failed
Test Reliability
Cypress flaky tests are particularly frustrating because Cypress has automatic waiting built in — so why are tests still timing out? The answer is usually one of three things: the test is waiting for the wrong thing, network requests are unpredictable, or state leaks between tests. This post walks through each