Webhooks

Use webhooks to automate custom flaky test workflows

Trunk provides webhooks for you to build custom integrations to automate workflows, like notifying your team when a test becomes flaky or automatically creating tickets to investigate flaky tests. Trunk already provides a Jira integration, and more are planned. Webhooks lets you build custom integrations for use cases that are not supported out of the box.

Svix powers webhooks for Trunk. You’ll be using Svix to configure webhooks and you should familiarize yourself with the Svix App Portal docs to learn more.

Supported Events

Trunk lets you create custom workflows with event-triggered webhooks. Flaky Test events are named with a test_case prefix. You can find all the events that Trunk supports in the event catalog:

Open resource

Open the referenced resource in a new tab.

Trunk publishes three Flaky Tests event types to Svix. Each event includes a full JSON schema with field descriptions visible in the Svix app portal.

test_case.monitor_status_changed

Emitted when a monitor activates or resolves for a test case.

Field	Type	Description
type	string	Always test_case.monitor_status_changed
timestamp	string (ISO 8601)	When the event occurred
monitor.id	string (UUID)	Unique identifier for the monitor
monitor.type	string	The type of monitor (e.g., pass_on_retry)
monitor.status	string	Current monitor status (active or resolved)
evidence	object	Data supporting the status change; structure varies by monitor type
repository.id	string (UUID)	Unique identifier for the repository
repository.html_url	string	URL of the repository
test_case.id	string (UUID)	Stable unique identifier for the test
test_case.name	string	Name of the test
test_case.classname	string	Test classname
test_case.file_path	string	File path of the test
test_case.html_url	string	URL to the test detail page in Trunk
test_case.codeowners	array of strings	Code owners associated with the test
test_case.quarantined	boolean	Whether the test is quarantined
test_case.variant	string	Test variant name

v2.test_case.status_changed

Emitted when a test case changes status (e.g., becomes flaky or is resolved), as triggered by a monitor.

Field	Type	Description
type	string	Always v2.test_case.status_changed
timestamp	string (ISO 8601)	When the event occurred
previous_status	string	The prior status of the test case
new_status	string	The updated status of the test case
triggered_by.monitor_id	string (UUID)	Unique identifier of the triggering monitor
triggered_by.monitor_type	string	Type of monitor that triggered the change
triggered_by.monitor_status	string	Status of the monitor at the time of the trigger
repository	object	See repository fields above
test_case	object	See test_case fields above

test_case.investigation_completed

Emitted when an AI-powered flaky test analysis finishes for a test case.

Field	Type	Description
type	string	Always test_case.investigation_completed
investigation_id	string (UUID)	Unique identifier for the investigation
confidence	number	Overall confidence score (0-1) for the findings
created_at	string (ISO 8601)	When the investigation completed
markdown_summary	string	Markdown-formatted summary of findings and recommendations
failure_message	string	The original failure message that triggered the investigation
facts	array	Facts discovered during the investigation
facts[].fact_type	string	Category of the fact (e.g., GIT_BLAME)
facts[].content	string	Detailed description with citations to supporting evidence
facts[].confidence	number	Confidence score (0-1) for this individual fact
repository	object	See repository fields above
test_case	object	See test_case fields above

You can also find guides for specific examples here:

Send a Slack Message				slack-integration
Create a GitHub Issue				github-issues-integration
Send a Microsoft Teams Message				microsoft-teams-integration
Create a Linear Issue				linear-integration