What causes ArtifactUploadFailure?

A transient network or storage service error during the artifact upload phase at the end of the run. The dbt Cloud environment storage quota was exceeded, preventing new artifact uploads. The run was cancelled or timed out before the artifact upload phase completed. A custom dbt Cloud agent or self-hosted orchestrator intercepted or terminated the process before upload

How do I fix ArtifactUploadFailure?

Step 1: Check the dbt Cloud run details log — artifact upload failures appear as a warning or error in the post-run phase.. Step 2: If the run was transient, re-run the job; dbt Cloud retries artifact uploads automatically on the next successful run.. Step 3: If using a custom orchestrator, ensure the dbt process is not killed before it completes the artifact upload step.. Step 4: Check dbt Cloud status (status.getdbt.com) for any storage or platform incidents at the time of failure.. Step 5: For dbt Explorer to reflect the latest state, trigger a manual documentation job run after the next successful production run.

Medium severityexecution

Power BI Refresh Error:
ArtifactUploadFailure

What does this error mean?

A dbt Cloud job run completed its dbt commands but failed to upload the generated artifacts (manifest.json, run_results.json, catalog.json) to dbt Cloud storage, causing dbt Explorer, dbt Docs, and source freshness features to show stale data.

Common causes

1A transient network or storage service error during the artifact upload phase at the end of the run
2The dbt Cloud environment storage quota was exceeded, preventing new artifact uploads
3The run was cancelled or timed out before the artifact upload phase completed
4A custom dbt Cloud agent or self-hosted orchestrator intercepted or terminated the process before upload

How to fix it

1Step 1: Check the dbt Cloud run details log — artifact upload failures appear as a warning or error in the post-run phase.
2Step 2: If the run was transient, re-run the job; dbt Cloud retries artifact uploads automatically on the next successful run.
3Step 3: If using a custom orchestrator, ensure the dbt process is not killed before it completes the artifact upload step.
4Step 4: Check dbt Cloud status (status.getdbt.com) for any storage or platform incidents at the time of failure.
5Step 5: For dbt Explorer to reflect the latest state, trigger a manual documentation job run after the next successful production run.

Frequently asked questions

Does an artifact upload failure mean my dbt models did not run?

No. The transformations executed successfully. The artifact upload is a post-run metadata step. Your tables and views are up to date; only the dbt Explorer, Docs, and source freshness UI will show stale information.

How do I manually trigger an artifact refresh in dbt Cloud?

Run a dbt compile or dbt docs generate job in the affected environment. Successful completion re-uploads the manifest and catalog artifacts, refreshing dbt Explorer and Docs.