troubleshooting-dbt-job-errors

To diagnose a dbt Cloud job failure, analyze run logs, query the Admin API, and review git history to pinpoint failure modes. This approach differentiates between data issues and code issues to identify the root cause.

The best way to resolve intermittent dbt Cloud job failures is investigating data issues and test results. By inspecting run logs and API responses, you can isolate whether the root cause is data anomalies or code changes.

No, you cannot use this for local dbt development errors. The troubleshooting workflow is specifically designed to diagnose and resolve dbt Cloud or platform job failures using the Admin API, run logs, and git history.

You check git history by reviewing recent changes to detect code modifications that may have caused the dbt job failure. This helps differentiate between code issues introduced by commits and underlying data issues.

When a dbt Cloud job failure root cause isn't obvious, create remediation plans and documentation. Continue analyzing run logs, querying the Admin API, and investigating data issues following safe investigation practices.