Events in the dashboard

The Events page is where you manage event definitions and their property schemas, and where you explore event volume and violations.

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The events list

Each row shows:

• Name — the event identifier
• Value type — currency, count, rate, boolean
• Recent volume — events per hour
• Schema status — number of properties, schemaEnforcement mode, violation rate
• Source — synced (CLI), dashboard-only, or auto-discovered

Sort by recent volume to see what’s actually flowing. Filter by source to find auto-discovered events that should be properly defined.

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Event detail

Clicking an event opens its detail page with several tabs.

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Overview

• Value type, unit, description
• Schema version and enforcement mode
• Volume sparkline
• Top properties by usage
• Currently-attached property groups

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Properties

The list of declared properties with their types, constraints, and dimension: true flag. If the event is synced from .traffical/config.yaml, properties are read-only — edit them in code. If it’s dashboard-only, you can add, edit, or delete properties here.

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Violations

If schemaEnforcement is warn or reject, the violations tab shows:

• Total violations in the last 24 hours / 7 days
• Breakdown by property and violation code
• Sample payloads for each violation type

Use this to find bugs in your track() code before promoting schemaEnforcement to reject.

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Schema versions

The full version history of the event’s schema with diff between consecutive versions. Old events validated against old versions are still readable; new events validate against the current version.

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Property groups

The Property groups sub-page lists all property groups in the project. Click a group to see its properties and which events reference it. Editing a group affects every event using it on next bundle refresh. See Type-safe events for how property groups work end-to-end.

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Event explorer

The explorer lets you query event volume by dimension.

• Pick an event
• Filter by any property
• Group by any property marked dimension: true
• Time range

It’s the closest thing to a SQL query without writing SQL. Useful for ad-hoc questions like “how many add_to_cart events came from the US last week, broken down by category?” For deeper analysis, route the same events into your data warehouse via SDK sync and query there.

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Best practices

• Define schemas as soon as an event matters. Auto-discovered events are fine in development; in production you want explicit schemas so the dashboard knows which fields are dimensions and the SDK type-checks track() calls.
• Mark dimensions explicitly. Properties used for breakdowns and metric slicing need dimension: true. The pipeline ignores non-dimension fields for aggregation purposes.
• Start with schemaEnforcement: warn. Watch the violations tab for a week or two. When the rate is essentially zero, flip to reject.

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Next steps