Test Automation

9 Best Flaky Test Detection Tools QA Teams Should Use in 2025

Detecting flaky tests is crucial for QA efficiency. This guide reviews the 9 Best Flaky Test Detection Tools for 2025, comparing solutions like TestDino and Trunk.io. These modern platforms offer AI-driven analysis and automated quarantine to cut flaky failures and ensure stable CI/CD pipelines.

Pratik Patel

Oct 30, 2025

9 Best Flaky Test Detection Tools in 2025 List

Flaky tests waste 6 to 8 hours of engineering time every week. They block CI pipelines, trigger false alarms, and force teams to rerun builds multiple times just to get a green light.

Poor software quality costs US organizations an estimated $319 billion, with testing identified as the weakest link. When teams can't trust their tests, they either waste time investigating false failures or, worse, ignore real issues that slip through.

In this guide, we’ll compare the best flaky test detection tools available in 2025, highlighting which ones will help you ship faster.

Why Flaky Test Detection Matters?

A flaky test is any test that passes and fails intermittently without code changes. Simple definition, expensive problem .

False failures waste hours while real defects go unseen. Many teams lose 6 to 8 hours a week chasing flakes. Every rerun adds to the bill, so flaky retries take a big share of CI spend, especially with weak test infrastructure.

You need tools that automatically detect patterns, flag unstable tests, and provide clear signals about what needs to be fixed.

Top Flaky Test Detection Tools

These nine platforms represent the most effective solutions for detecting and managing flaky tests in 2025. Each brings unique strengths to the challenge of identifying intermittent test failures.

TestDino: Leverages machine learning to distinguish between genuine bugs and flaky failures in Playwright tests, providing root-cause analysis in seconds.
Currents: Combines cloud-based test storage with intelligent orchestration to detect flaky Playwright tests.
Trunk.io: Operates as a flaky test quarantine system across programming languages to keep CI pipelines green.
DataDog: Extends observability into testing, correlating flaky tests with infrastructure metrics.
BrowserStack Test Observability: Uses its device cloud to expose environment-specific flakiness.
LambdaTest Test Analytics: Applies ML algorithms to test execution data for detecting flakiness patterns.
ReportPortal: An open-source solution with ML capabilities for flaky test analysis.
Microsoft Playwright Testing Preview: Provides Azure-native cloud execution that scales Playwright tests.
Allure TestOps: Bridges manual and automated testing workflows, using stability analytics to identify flaky tests.

Overview of the Top Flaky Test Detection Tools

	TestDino	Currents	BrowserStack	Allure TestOps	LambdaTest
Getting Started
Pricing	$39/month	$49/month	$39/month	$39/month	$25/month
Best for	Playwright Reporting & Analytics	Dashboards & Orchestration	Analytics & Reporting	Test management	Test Analytics
Framework support	Playwright	Playwright	Playwright & More	Playwright & More	Playwright & More
Ease of use
Key Features
AI Failure Classification
Confidence Score with AI
Root Cause Analysis
Test Run Summary
Flakiness Detection
Trace Viewer
Visual comparison
Cross-Environment Analysis
Historical Trend Analysis
Branch and PR Analytics
Business Impact
Time Saved per Sprint	6–8 hrs	2–3 hrs	4–5 hrs	3–4 hrs	3–4 hrs
Release Speed Improvement	12–20%	5–10%	10–15%	8–12%	8–12%
Reduction in Flaky Failures	50–70%	30–50%	40–60%	25–30%	25–30%

Pricing

$39/month

Best for

Playwright Reporting & Analytics

Framework support

Playwright

Ease of use

Key Features

AI Failure Classification

Confidence Score with AI

Root Cause Analysis

Test Run Summary

Flakiness Detection

Trace Viewer

Visual comparison

Cross-Environment Analysis

Historical Trend Analysis

Branch and PR Analytics

Business Impact

Time Saved per Sprint

6–8 hrs

Release Speed Improvement

12–20%

Reduction in Flaky Failures

50–70%

Pricing

$49/month

Best for

Dashboards & Orchestration

Framework support

Playwright

Ease of use

Key Features

AI Failure Classification

Confidence Score with AI

Root Cause Analysis

Test Run Summary

Flakiness Detection

Trace Viewer

Visual comparison

Cross-Environment Analysis

Historical Trend Analysis

Branch and PR Analytics

Business Impact

Time Saved per Sprint

2–3 hrs

Release Speed Improvement

5–10%

Reduction in Flaky Failures

30–50%

Pricing

$39/month

Best for

Analytics & Reporting

Framework support

Playwright & More

Ease of use

Key Features

AI Failure Classification

Confidence Score with AI

Root Cause Analysis

Test Run Summary

Flakiness Detection

Trace Viewer

Visual comparison

Cross-Environment Analysis

Historical Trend Analysis

Branch and PR Analytics

Business Impact

Time Saved per Sprint

4–5 hrs

Release Speed Improvement

10–15%

Reduction in Flaky Failures

40–60%

Pricing

$39/month

Best for

Test management

Framework support

Playwright & More

Ease of use

Key Features

AI Failure Classification

Confidence Score with AI

Root Cause Analysis

Test Run Summary

Flakiness Detection

Trace Viewer

Visual comparison

Cross-Environment Analysis

Historical Trend Analysis

Branch and PR Analytics

Business Impact

Time Saved per Sprint

3–4 hrs

Release Speed Improvement

8–12%

Reduction in Flaky Failures

25–30%

9 Best Flaky Test Detection Tools

1. TestDino

Best for:

Playwright teams that need AI test reporting to automate failure triage, flag flaky tests, and ship faster.

About TestDino:

TestDino is an AI-powered reporting & analytics platform for Playwright test suites. It centralizes test results from CI pipelines and extracts Git/PR context to provide release metrics and failure summaries

How it detects flaky tests:

TestDino automatically flags flaky tests by analyzing Playwright test outcomes across retries within the same CI commit.
TestDino's AI reviews test history, error logs, branch context, and environment metadata to distinguish genuine code failures from intermittent flakiness.
The system calculates flakiness percentage based on inconsistent outcomes and groups tests by root cause: timing issues, network problems, environment failures, element not found, or intermittent assertions.

Strengths:

Playwright-native with one-step CI setup, and Git-aware checks update branches and PRs automatically.
AI insights separate actual bugs from unstable tests, and track trends for flakiness, retries, and duration.
Unified evidence and integrations: logs and screenshots in one place, with Jira/Linear ticketing and Slack alerts.

Areas to Improve:

Limited framework support: currently only supports Playwright, with Selenium still in development.

Standout Capability:

ML-based failure categorization with smart fix suggestions. Essentially a "senior developer in a box" that learns from test logs to instantly identify flaky tests and provide actionable next steps.

Pricing:

Four tiers: Community (free for 5,000 runs, single user), Pro ($39/month for 25,000 runs, 5 users), Team ($69/month for 100,000 runs, 30 users), and Enterprise (custom). Pro and Team include AI insights, Jira and Slack integration, and longer data retention. Enterprise adds SSO and 24/7 support. Good fit for Playwright teams scaling test coverage.

2. Currents

Best for:

Teams running large Playwright suites that need speed and stability.

About Currents.dev:

Currents.dev is a cloud-based reporting solution for Playwright that stores and visualizes all test artifacts. It provides historical analysis and debugging tools while offering intelligent test orchestration for faster execution.

How it detects flaky tests:

Currents uses Playwright's built-in retry mechanism for instant flaky detection.
When a test fails on the first attempt but passes on retry, Currents immediately badges it as flaky.
When a test fails on the first attempt but passes on retry, Currents immediately badges it as flaky.

Strengths

Comprehensive artifact storage with logs, screenshots, and traces in one place.
Native parallel test orchestration balances test chunks across runners for 50% speed improvement.
Quarantine capability isolates flaky tests from blocking pipelines.

Areas to Improve:

Supports only JavaScript-based frameworks (Playwright/Cypress) with no support for other languages.
No free tier or self-hosted option available, which may deter smaller teams or those with strict data residency requirements.
Limited integrations beyond CI/CD - lacks native connections to popular issue trackers like Jira or project management tools.

Standout Capability:

Integration of cloud dashboard with built-in Playwright orchestration and flaky test quarantining. Few tools combine instant flaky detection with test balancing and rich trace capture.

Pricing:

It offers two plans: Team ($49/month for 10k test results and up to 10 users; $5 per extra 1k) and Enterprise (custom). This fits Playwright/Cypress teams that outgrow basic storage; it might not suit you if costs need to stay flat as volume spikes.

3. Trunk.io

Large codebases that need to keep CI green while fixing flaky tests.

Best for:

Large codebases that need to keep CI green while fixing flaky tests.

About Trunk.io:

Trunk is a language-agnostic test stability platform for eliminating flaky tests. It aggregates results from multiple CI systems and provides analytics on test stability trends with ticketing system integration.

How it detects flaky tests:

Trunk detects flaky tests through statistical analysis of CI results across multiple runs of the same commit.
When a test's final status differs between runs on stable branches, Trunk flags it as flaky.
The system needs approximately 10 historical runs per test to establish confidence.

Strengths:

Universal support works across all languages, test frameworks, and CI providers.
AI-powered failure clustering groups similar failures and tracks stability score trends.
Auto-quarantine feature with automatic GitHub issue creation ensures flakes are tracked and fixed.

Areas to Improve:

Requires significant historical data (10+ runs per test) before accurate flaky detection begins, delaying initial value.
No built-in test execution capabilities - only analyzes results from other tools, requiring additional infrastructure
A complex pricing model based on test volume and team size that can become expensive for large test suites.

Standout Capability:

Flaky-test focus that detects, quarantines, and auto-triages flakies for any test suite. The combination of AI clustering and seamless issue integration across all languages and frameworks is unique.

Pricing:

Three tiers - Free ($0 for up to 5 committers), Team ($18 per committer/month), and Enterprise (custom). Per-committer pricing scales with team size, which may not be ideal if you prefer fixed org-level fees.

4. Datadog

Best for:

Organizations that need policy, alerts, and trends across many repos.

About Datadog:

Datadog CI Visibility extends Datadog's observability platform into CI/CD testing. It correlates test results with logs, metrics, and traces across services for comprehensive debugging and monitoring.

How it detects flaky tests:

Datadog automatically tags tests as flaky when they show both passing and failing statuses for the same commit across multiple runs.
Its Early Flake Detection feature proactively retries new tests up to 10 times. Any failure during these retries immediately marks the test as flaky.
The system distinguishes between new flaky tests (just started flaking) and known flaky tests (recurring issues).

Strengths:

Quality Gates prevent flaky or failing code from shipping automatically.
Enterprise-scale monitoring across multiple repositories and services.

Areas to Improve:

Enterprise pricing can exceed $100K annually for large organizations, making it inaccessible for smaller teams.
Steep learning curve with complex setup requiring instrumentation across multiple services and frameworks.
Limited standalone value, most effective when already using Datadog's full observability suite, increasing total cost.

Standout Capability:

Unifying testing with full-stack observability. Test failures tie back into Datadog's metrics and tracing, providing end-to-end linkage of tests with production telemetry.

Pricing:

Datadog has Usage-based pricing, API tests start at $5 per 10,000 runs/month, browser tests at $12 per 1,000 runs/month, and mobile app tests at $50 per 100 runs/month (annual billing; higher on-demand). This suits data-driven teams already on Datadog; it might not be the best option if you want a simple seat price.

5. BrowserStack Test Observability

About BrowserStack Test Observability:

BrowserStack Test Observability is an analytics layer that aggregates results from all test frameworks and environments. It provides cross-browser/device visibility and integrates results from disparate CI systems into customizable dashboards.

How it detects flaky tests:

BrowserStack uses AI-driven Smart Tags to automatically detect flaky tests by examining result histories across real devices and browsers.
Any test showing inconsistent pass/fail outcomes over time gets tagged as "Flaky" automatically.
The system analyzes patterns across different environments, browser versions, and device combinations.

Strengths:

Tracks all automated tests (UI, API, or unit) in one place, not just BrowserStack runs
Timeline debugging helps identify exactly when tests became flaky
Quality gates and metrics let teams set pass/fail criteria on stability trends

Areas to Improve:

Requires SDK integration for each test framework, adding maintenance overhead and potential compatibility issues.
Separate pricing from BrowserStack's testing cloud means additional costs even for existing customers.
Performance impact is reported when uploading large test suites with extensive logs and screenshots.

Standout Capability:

AI-powered failure diagnostics with enforceable quality gates. Not only highlights flaky tests but lets teams build custom gates that block merges based on stability criteria.

Pricing:

Free start plus paid tiers; exact prices are not public, so contact sales. Good fit if you already use BrowserStack and want a unified contract; less handy if you need published numbers for quick procurement.

6. LambdaTest Test Analytics

Best for:

Teams running Selenium/Cypress/Playwright on LambdaTest that want AI flaky analytics.

About LambdaTest Test Analytics:

LambdaTest Test Analytics leverages ML within the LambdaTest cloud platform to analyze test stability. It provides specialized widgets, including Flakiness Trends graphs and Severity Summaries for comprehensive test health monitoring.

How it detects flaky tests:

LambdaTest Test Intelligence offers two ML-powered detection modes
Command Logs Mapping mode compares step-by-step logs across runs and flags tests with inconsistent command outcomes
Error Message Comparison mode only flags tests that fail with different error messages on separate runs. Tests need at least 10 runs to qualify for detection.

Strengths:

Rich visualization with customizable dashboards for trends, severity, and group views.
Integrated seamlessly with LambdaTest's testing cloud for cross-browser coverage.
Automatic prioritization of flaky tests based on impact and frequency.

Areas to Improve:

Locked to the LambdaTest platform - cannot analyze tests run outside their cloud infrastructure.
A minimum of 10 test runs is required before flaky detection activates, which delays insights for new or infrequently run tests.
Limited customization options for flakiness thresholds and detection rules compared to dedicated tools.

Standout Capability:

End-to-end integration with the LambdaTest environment and AI insights. Automated flaky detection with trending dashboards inside the testing platform.

Pricing:

Overall platform pricing scales by parallel sessions; specific pricing for Test Intelligence/Analytics is not posted, so request a quote. Works well for teams standardizing on LambdaTest; may not suit buyers seeking analytics as a separately priced add-on.

7. ReportPortal

Best for:

Teams that want self-hosted analytics and ML triage.

About ReportPortal:

ReportPortal is an open-source automation dashboard that unifies historical test data across frameworks. It features customizable widgets and provides granular tracking of ongoing suite health with AI-assisted failure analysis.

How it detects flaky tests:

ReportPortal identifies flaky tests through its Flaky Test Cases Table widget, which tracks status switches across launches.
A test appears as flaky when its final status flips between Passed and Failed within your specified launch window (2-100 launches, default 30).
The widget only considers the last retry status of each test. Once configured, the widget auto-updates to show your most unstable tests based on their flip frequency.

Strengths:

Machine learning automatically triages failures and categorizes them by type.
Easy integration with common CI tools and frameworks with strong automation support.
Self-hosted deployment gives teams full control over data and customization.

Areas to Improve:

Browser compatibility issues with UI working properly only on Chrome and Firefox, limiting accessibility.
Performance degradation with large parallel test suites (1000+ concurrent tests) requires infrastructure scaling.
Manual test support is incomplete, with missing features for test case management and environment configuration.

Standout Capability:

Open-source nature and customizability. It has dashboard customization and AI-assisted analysis with self-hosted flexibility.

Pricing:

SaaS offers Startup ($569/month), Business ($2,659/month), and Enterprise (custom); a free self-hosted community edition and on-prem support packages are also available. Managed SaaS suits teams that want hosting and SLAs, while small teams may find the Startup tier more than they need.

8. Microsoft Playwright Testing Preview

Teams in the Microsoft/Azure stack running Playwright at scale

About Microsoft Playwright Testing Preview:

Microsoft Playwright Testing Preview is a managed Azure service that abstracts away test infrastructure. It handles browser provisioning and artifact storage automatically while providing massive parallelization across browser/OS combinations.

How it detects flaky tests:

Microsoft's service automatically marks tests as flaky using Playwright's native retry logic.
Microsoft's service automatically marks tests as flaky using Playwright's native retry logic.
Detection works automatically when you send run results to the service, with no additional setup beyond standard Playwright retries.

Strengths:

No code modifications needed for existing Playwright suites.
Built-in reporting captures failure details, videos, and traces automatically.
Seamless integration with Azure DevOps and other Microsoft tooling.

Areas to Improve:

Preview status with planned retirement in 2026, creating uncertainty about long-term viability and migration paths.
Azure lock-in with no support for other cloud providers or on-premise deployment options.
Limited features compared to mature tools - basic reporting without advanced analytics or AI-powered insights.

Standout Capability:

A cloud-native Playwright execution service. Scale Playwright tests in Azure by offloading execution to the cloud and managing all browsers/OS combinations automatically.

Pricing:

Their 30-day free trial includes 100 test minutes and 1,000 test results; afterward, pay-as-you-go per test minute and per 1,000 results. Best for Azure-centric teams; not ideal if you require a fixed monthly price cap.

9. Allure TestOps

Best for:

Teams that need sophisticated test management with manual flaky test muting.

About Allure TestOps:

Allure TestOps is a centralized quality management system that connects manual and automated test results into unified workflows. It automatically imports results to generate live documentation and dashboards while linking test runs to test cases and defects.

How it detects flaky tests:

Allure TestOps identifies flaky tests through stability analytics rather than automatic tagging.
It calculates each test's success rate over recent launches and surfaces intermittent failures in its "Top Test Cases" widget.
You define the analysis window (time period or launch count), and Allure updates the unstable test report automatically.

Strengths:

Works with popular CI servers, automatically publishing Allure-formatted reports.
Unified manual and automated test handling in a single, consistent UI.
Comprehensive test case management with requirement traceability.

Areas to Improve:

Manual testing module limitations, including the inability to edit test results after execution or to predefine environments.
Global configuration scope for custom fields causes confusion in multi-project organizations.
Relatively high per-user licensing costs compared to alternatives, especially for large QA teams.

Standout Capability:

Automated linking of test results to test cases and documentation. Auto-creating manual test cases from automated runs ensures documentation is always up-to-date.

Pricing:

Their cloud starts at $39/user/month with volume discounts down to $30/user/month; Server is $39/user/month for 5–50 users, larger deployments are custom. Per-user pricing suits organizations that align costs to active users.

Why Choose TestDino For Flaky Tests Detection

You get clear signals on what failed and why, so triage is quick. Role-aware dashboards and PR views keep reviewers in flow. Setup is simple because it ingests Playwright's default output.

1. Ingest and label the run

Reads the Playwright report from CI, builds a single Test Run with Passed, Failed, Flaky, and Skipped.
Adds AI labels per failure: Unstable, Actual Bug, UI Change, or Miscellaneous.

2. Group flaky tests by cause

Splits flakies into Timing-related, Environment-dependent, Network-dependent, Intermittent assertion, and Other.

3. See attempts and evidence

Shows each retry with its own error text, screenshots, and console. A pass after a fail on the same code is a strong flaky signal.
Surfaces the primary reason, for example timeout or element not found.

4. AI insights for fast triage

Summarizes error variants, applies AI categories, and highlights New Failures, Regressions, and Consistent Failures.
The test-case view shows category + confidence score with recommendations, and recent history.

5. Trends expose hidden flakiness

History plots Passed, Failed, Flaky, Skipped across recent runs and flags spikes in flaky share.
Analytics adds average flakiness, new failure rate, and retry trends.

6. PR-aware workflow

Pull Requests view shows the latest run per PR with passed, failed, flaky, skipped counts, and quick links to evidence.

7. One-click handoff and alerts

Create Jira or Linear issues prefilled with test details, failure cluster, code snippet, short history, and links.
Slack posts run status, success rate, passed, failed, flaky, skipped, branch, author, and a "View run" link.

8. CI setup

Add the Playwright JSON reporter, upload from CI with the CLI or the GitHub Action. Labels and flaky breakdowns appear automatically.

Conclusion

Flaky tests destroy productivity and trust.The right detection tools change them from pipeline blockers into manageable issues. Whether you choose AI-powered analysis, CI-native controls, or open-source dashboards, the key is starting now.

If you want simple, accurate flaky detection for Playwright with real cause hints and alerts, TestDino is a strong choice for teams in 2025. It flags flaky tests, explains why, and integrates with your CI and chat tools with minimal setup.

Try TestDino free for 14 days and measure the reduction in debugging time yourself. Sign up today to see which TestDino plan fits your needs.

FAQs

A test is considered flaky when it sometimes passes and sometimes fails without any changes to the code or test itself. This inconsistent behavior is usually due to timing issues, network glitches, environment differences, or other intermittent factors.