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title Dashboards
description Create custom dashboards with real-time metrics powered by TRQL queries.

Overview

In the Trigger.dev dashboard we have built-in dashboards and you can create your own.

Dashboards are powered by TRQL queries with widgets that can be displayed as charts, tables, or single values. They automatically refresh to show the latest data.

Available metrics data

Trigger.dev automatically collects process metrics (CPU, memory) and Node.js runtime metrics (event loop, heap) for all deployed tasks -- no configuration needed. Requires SDK version 4.4.1 or later. You can also create custom metrics using the otel.metrics API from the SDK.

All of this data is available in the metrics table for use in dashboard widgets. See Logging, tracing & metrics for the full list of automatic metrics and how to create custom ones, or the Query page for the metrics table schema.

The built-in Metrics dashboard

Visualization types

  • Line chart - Show trends over time
  • Bar chart - Compare values across categories
  • Area chart - Display cumulative trends
  • Table - Show detailed data in rows
  • Single value - Display a single metric (count, sum, average, etc.)

You can also add Titles to your dashboard.

Filtering and time ranges

All widgets on a dashboard use the time range filter applied to the dashboard.

You can also filter the data by:

  • Scope: Environment, Project, Organization
  • Tasks
  • Queues

Creating custom dashboards

  1. In the sidebar click the + icon next to "Dashboards".
  2. Name your custom dashboard.
  3. From the top-right you can "Add chart" or "Add title".
  4. For charts you write TRQL queries and choose a visualization type.
  5. You can resize and reposition widgets on your dashboards.

Performance considerations

Optimize queries for metrics

  1. Use time bucketing - timeBucket() automatically groups by appropriate intervals
  2. Limit result size - Add LIMIT clauses, especially for table widgets
  3. Use approximate functions - uniq() instead of uniqExact() for faster approximate counts

Exporting metric data

Export data from any metric widget:

  1. Click the widget menu (three dots)
  2. Select "Copy JSON" or "Copy CSV"

Best practices

  1. Start simple - Begin with basic metrics and iterate based on insights
  2. Use meaningful names - Give widgets clear, descriptive titles
  3. Group related metrics - Organize dashboards by theme (performance, costs, errors)
  4. Test queries first - Use the Query page to develop and test before adding to dashboards

Troubleshooting

Widget shows "No data"

  • Check that your query returns results in the Query page
  • Verify time filters include the period with data
  • Ensure task/queue filters match existing runs

Widget is slow to load

  • Add time range filters to your query
  • Use LIMIT clauses
  • Simplify aggregations
  • Check query execution time in Query page

Chart displays incorrectly

  • Verify column names match visualization config
  • Check data types (numbers for charts, dates for time series)
  • Ensure timeBucket() is used for time-series charts
  • Review that series columns exist in query results

Limits

Dashboards are powered by Query so have the same limits as Query.

There is a separate concurrency limits for metric widgets.

Limit Details
Concurrent widget queries 30 per project

See Limits for details.