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Monitor dbt State activity Preview

Learn how to monitor dbt State activity in dbt platform for better visibility into model builds and cost savings.

dbt State monitoring helps you:

  • Track effectiveness of dbt State — See how dbt State reduces unnecessary model rebuilds by only building models when there are changes to the data or code. dbt State provides transparency into how the optimization works across your projects.
  • Analyze build patterns — Gain insights into your project's build frequency and identify opportunities for further optimization.

dbt State metrics​

When you go to Account settings > Billing & Usage > Usage-based features, the State tab shows how many days remain in your trial period. Once dbt State is enabled, it displays the following for the current month:

  • Models reused this month: How many model builds dbt State skipped or cloned instead of rebuilding from scratch.
  • Total % build reduction: The overall reduction in model builds across your account.
  • Total query run time reduction: The total time dbt State saved by not executing unnecessary model builds.

The State tab also displays the following charts:

  • DATT — Shows the target tables processed by dbt State, split into Billable and Free. Daily active target tables (DATTs) are the billable units for dbt State. During a trial, all DATTs are counted as free.
  • Asset builds — Shows all model builds for the month, including models reused and cloned.

Models built and reused chart​

When you go to your Account home, you'll see a chart showing the number of models built and reused, giving you visibility into how dbt State is optimizing your data builds. You can also view the number of reused models per project on Account home.

Logs view of built models​

When you run a job, or when you run dbt run or dbt build locally, a structured logs view shows which models were built, skipped, or reused.

Logs view of built modelsLogs view of built models
  1. Each model has an icon indicating its status.
  2. The Reused tab indicates the total number of reused models.
  3. You can use the search bar or filter the logs to show All, Success, Warning, Failed, Running, Skipped, Reused, or Debugged messages.
  4. Detailed log messages provide context on why models were built, reused, or skipped. These messages are highlighted in the logs.

Reused tag in the Latest status lens​

Lineage lenses are interactive visual filters in dbt Catalog that show additional context on your lineage graph to understand how resources are defined or performing. When you apply a lens, tags become visible on the nodes in the lineage graph, indicating the layer value along with coloration based on that value. If you're significantly zoomed out, only the tags and their colors are visible in the graph.

The Latest status lens shows the status from the latest execution of the resource in the current environment. When you use this lens to view your lineage, dbt State tags reused models with Reused.

Latest status lens showing reused modelsLatest status lens showing reused models

To view your lineage with the Latest status lens:

  1. From the main menu, go to Orchestration > Runs.
  2. Select your run.
  3. Go to the Lineage tab. You'll see your project's lineage.
  4. In the Lenses field, select Latest status.

Explain tab​

To see why dbt State rebuilt, reused, or cloned a specific resource, go to Orchestration > Runs. Select a run and go to the Explain tab.

The Explain tab appears on job runs that used dbt State. It shows why dbt State rebuilt, reused, or cloned each resource, so you can investigate unexpected behavior or verify that State is working as expected. The tab is available while a run is in progress and updates as resources finish.

The tab displays an Explain results table with one row per resource. You can search by resource name and download the full results as a text file.

Expand a row to see the full decision details. Not all analyses apply to every resource type:

FieldDescription
Resource nameThe name of the resource.
Resource typeThe resource type: model, seed, snapshot, test, and so on.
DecisionThe reason dbt State rebuilt, reused, or cloned this resource.
Run stepThe job command that ran this resource (for example, dbt build --exclude tag:ml_pipeline).
Table analysisWhether the target table already exists in the schema.
Query analysisWhether the resource query or its upstream queries have changed.
Data freshness analysisWhether upstream data is fresh or within the configured lag_tolerance.
Explain tab showing the decision breakdownExplain tab showing the decision breakdown

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