Log developer tasks for metric anomalies

When a critical performance threshold is crossed in Watershed LRS, automatically create an issue in GitHub so engineering can investigate immediately.

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How Knit builds this workflow

The Agent researches both APIs and wires the trigger on one side to the action on the other — no pre-built connector required. Here is the vocabulary it has to work with.

Watershed LRS Explore Watershed LRS →

Triggers

Report created

Fires when a new report or dashboard is created in Watershed LRS.

Metric threshold crossed

Fires when a tracked metric in Watershed LRS crosses a set threshold.

Scheduled report ready

Fires when a scheduled report finishes generating in Watershed LRS.

Actions

Refresh dashboard

Creates or refreshes a dashboard in Watershed LRS.

Export report

Exports a report from Watershed LRS.

Send alert

Sends an alert when a metric changes in Watershed LRS.

GitHub Explore GitHub →

Triggers

New issue captured

Fires when a new error or issue is captured in GitHub.

Issue status changed

Fires when an issue's status changes in GitHub.

Deployment tracked

Fires when a new deployment is tracked in GitHub.

Actions

Create issue

Creates or updates an issue in GitHub.

Assign issue

Assigns an issue in GitHub to a teammate.

Resolve issue

Resolves or mutes an issue in GitHub.

Refresh business dashboards after code deployments When a new software deployment is tracked in GitHub, immediately refresh your key performance dashboards in Watershed LRS. See details

Alert team leads when critical bugs are resolved When an issue status changes to resolved in GitHub, send an alert through Watershed LRS to keep stakeholders informed. See details

See all Watershed LRS + GitHub integrations → · Browse the full workflow library →

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FAQ

Common questions

Can Knit build “Log developer tasks for metric anomalies” between Watershed LRS and GitHub?

Yes — describe it in the box above and Knit's Integrations Agent researches Watershed LRS and GitHub's public API docs (or your own uploaded docs) and builds a working workflow, whether or not either app already has a pre-built connector.

How long does it take to build?

Minutes to a first working version, not weeks — you test it against real data before it goes anywhere near production.

Why connect metric alerts in Watershed LRS to developer workflows in GitHub?

When key business or system metrics breach defined thresholds in Watershed LRS, creating a ticket in GitHub ensures engineering addresses root causes immediately.

Can software deployments in GitHub update data in Watershed LRS?

Yes, tracking a new release in GitHub can prompt Watershed LRS to refresh relevant dashboards so you can analyze post-deployment impact instantly.