Understand the State of a dbt Schedule
This user guide will show you how you can monitor your dbt Schedules and its dependent end-to-end pipelines. Understanding the state of your dbt Schedule will help you with any troubleshooting that may be required.
dbt Schedule Page
The specific dbt Schedule page is the best place to view its state.
The header of the dbt Schedule page provides 2 metrics about the state of the schedule on a quick glance.
- Last dbt Build: Shows the time since the last successful dbt build.
- Last Run Time: Shows how long the last successful dbt build took.
To view more specific details about each dbt Schedule run, go to the Activities tab.
Activities
The Activites tab provides information about each dbt Schedule trigger, it’s pipeline activites and the dbt build.
Each dbt Schedule run consists of the following 3 steps:
Build Trigger
When the cron condition of a dbt Schedule is met, the schedule triggers all involved pipelines to check for new data.
Pipeline Activities
After a dbt Schedule triggers all its pipelines, they check for new data and start ETLing. In the pipelines activities step you can see the progress of the depending pipelines. By clicking View details you can see a list of all the depending pipelines and whether the pipeline is still running, has finished or no new data.
If the dbt Schedule does not have pipelines that its models depend on or there was no new data found in the pipeline sources this will show “No pipelines to load”.
dbt Build
This is the actual dbt build itself that runs the dbt models in your Data Warehouse. This step will show how long the build took and whether it succeeded. The dbt build will be skipped if one or more of the involved pipelines failed to process the new data or all of the pipelines had no new data and the skip if no new data setting was enabled.
After the build finished, this step shows how many of the models ran successfully.
You can view the full dbt build log output by clicking on View log.
Logs
You can view the full dbt log output of each dbt Schedule build.
The logs are aggregated when running dbt build for a dbt Schedule.
The logs provide detailed information about which models were run as part of the build and whether the model runs succeeded. They also show whether the tests in your project ran successfully.
If a dbt build did not succeed, the logs will provide error messages about the build failure.