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Metric alerts

A metric alert watches a number on a dashboard and notifies you when it crosses a limit you set — no need to keep the dashboard open.

  1. Open the dashboard and find a KPI card with the value you want to watch.
  2. From the card’s menu, choose Create alert.
  3. Set the condition — above or below a threshold value — and give the alert a name.
  4. Configure the evaluation schedule (e.g. hourly, daily) and choose your preferred notification channels.
  5. Save. The alert is active immediately.

You only need view access to the dashboard; alerts are personal — the ones you create notify you.

Alerts are evaluated server-side on a schedule (a background evaluation worker, not your browser), so they fire whether or not you are logged in.

  • Security & RLS — each evaluation runs under the alert creator’s data permissions. If the model enforces row-level security, the alert sees exactly the rows you are allowed to see, never more.
  • Transition firing — an alert fires on the transition across your threshold: you are notified when the value crosses into the alert condition, avoiding duplicate spam on subsequent checks while it remains past the limit.
Channel What you get
In-app The bell icon and the Notifications page — newest first, with the metric name, threshold, fired value, timestamp, and a direct link to the dashboard. Supports mark read / Mark all read.
Email A notification message with the fired value and a deep link back to the dashboard view.
Webhooks An alert.fired event sent to any configured endpoint — including Slack-compatible webhook formats; see Webhooks.
  • Notifications history — past alert firing events and history are visible on the Notifications page.
  • Editing and deleting — manage your alert definitions via the Alerts API (GET, PUT, DELETE /api/dashboard-alerts/{id}).

The dashboard dialog watches the card’s rendered value. To watch a governed metric directly — one rule on the centralized definition, independent of any visual card — create the alert through the Alerts API with a metric-bound condition ({ metricId, operator, threshold }).

You can also ask the AI chat agent to create and monitor metric alerts for you using natural language.