# Configuring Source Freshness

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: <a href="#how-to-configure-source-freshness" id="how-to-configure-source-freshness"></a>

#### 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

{% hint style="info" %}
The `loaded_at_field` is required for freshness checking. Without it, dbt will skip freshness calculations for that table.
{% endhint %}

#### 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

{% hint style="info" %}
👉 See also: [freshness definition and configurations.](https://docs.getdbt.com/reference/resource-properties/freshness#definition)
{% endhint %}

### **Configuration Example**

{% code title="models/sources.yml" lineNumbers="true" %}

```yaml
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
```

{% endcode %}


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