Configuring Source Freshness

Set up and manage source data freshness checks in Bolt to maintain data quality and meet SLA requirements.

Monitor the freshness of your source data by configuring the dbt source freshness command in your Bolt schedules. This helps ensure your data meets defined SLAs and maintains quality standards.

Overview

When you include the dbt source freshness command in your schedule, Bolt tracks and reports the last update time of your source tables. This information appears in the Source Freshness section of your run details.

Configuration Steps:

1. Add Required Fields

To enable source freshness checking, add these elements to your source configuration:

• A freshness block to define timing thresholds

• A loaded_at_field to specify the timestamp column

The loaded_at_field is required for freshness checking. Without it, dbt will skip freshness calculations for that table.

2. Define Freshness Rules

In your freshness block, specify one or both timing thresholds:

• warn_after: Triggers a warning when data exceeds this age

• error_after: Marks data as error state when exceeding this age

👉 See also: freshness definition and configurations.

Configuration Example

models/sources.yml

sources:
  - name: analytics_raw
    freshness: # default freshness
      warn_after: {count: 12, period: hour}
      error_after: {count: 24, period: hour}
    loaded_at_field: fivetran_loaded_at

    tables:
      - name: orders
        freshness: # make this a little more strict
          warn_after: {count: 6, period: hour}
          error_after: {count: 12, period: hour}

      - name: customers # this will use the freshness defined above

      - name: product_skus
        freshness: null # do not check freshness for this table