Reduced time to flake detection

Configure independent detection monitors (threshold, pass-on-retry, and manual) with adjustable sensitivity and recovery periods to match your team's flake tolerance.
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When a high percentage of tests fail in a single run, treat it as an infrastructure failure rather than individual test failures
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View a timeline of recent test runs including pass/fail results, quarantine status, and status changes to understand how a test has behaved over time.

Mute, delete, and manually flag individual test monitors to control how tests are tracked and when alerts fire.

Track timing and reliability of GitHub Actions jobs and trigger alerts

Collections let you organize tests into logical groups (framework, application, etc) so you can configure detection rules and thresholds independently for each. Whether your Jest unit tests need stricter flake detection than your Playwright E2E suite, or different teams want their own reporting views, Collections give you the flexibility to match your CI reliability strategy to how your codebase is actually structured.

Trigger an Agent to investigate and fix build failures

Configure monitors to detect and label new tests, skipped tests, and slow tests.

Dispatch an AI agent to fix flaky tests as they're detected

A monitor that flags a test as flaky or broken when it accumulates a configured number of failures in a rolling window.

Filter merge queue health metrics by impacted targets to analyze performance for specific parts of your codebase
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Merge queue dashboard pages support updating automatically in real-time

Receive personalized Slack DMs about your PRs' progress through the merge queue
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Mark specific PRs to test individually without batching, ensuring if they fail, they don't take down other PRs with them
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Run independent merge queues for different branches in the same repository

Skip redundant testing and merge immediately when your PR is already up-to-date and the queue is empty
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Select preferred merge method (squash, rebase, merge) for your PRs going through the merge queue
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Reuse CI Job results when isolating failures in batched PRs to save CI resources
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Set higher test concurrency for failure isolation without slowing down your main merge queue
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Add an endpoint to allow users to scrape merge queue metrics for monitoring
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Programmatically create, configure, and manage merge queues via REST API
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We're building first-class support for deploying Trunk Merge Queue's data plane directly into your AWS account. For teams with strict data residency, compliance, or on-prem GitHub Enterprise requirements, you'll soon be able to run the Merge Queue entirely within your own infrastructure while we continue to manage the control plane, giving you enterprise-grade security and control without sacrificing the fully managed experience

Support for merging stacked PRs atomically

Trigger alerts on metrics like failure rate or expected time to merge

Configure trusted authors whose commits won't force queued PRs to restart testing

AI Agent for automatically resolving test failures and re-submitting PRs

Control your Trunk Merge Queue through Terraform

Support seamless integration with both GitHub rulesets and classical branch protection rules

Merge Queue will make it clear if anything about your current GitHub branch protection rules will interfere with Merge Queue working

Bring more Merge Queue functionality right into GitHub's UI

Allow users to force a PR to be admitted into the Merge Queue before it becomes mergeable, after which Merge Queue will merge the PR if it passes tests in the MQ, effectively bypassing GH branch protections