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Troubleshoot Jira ingestion

Beta

The Jira connector is in Beta.

This page describes common issues with the Jira connector in Databricks Lakeflow Connect and how to resolve them.

On-premises connection failures​

If your on-premises connection fails or data ingestion fails with an unreachable error, make sure Databricks IP addresses are allowlisted at your firewall.

General pipeline troubleshooting​

If a pipeline fails while executing, click the step that failed and confirm whether the error message gives sufficient information about the nature of the error.

View pipeline event logs in the UI

You can also check and download the cluster logs from the pipeline details page by clicking Update details in the right-hand panel, then Logs. Scan the logs for errors or exceptions.

View pipeline update details in the UI

Common error codes​

403 Unauthorized​

Resolution:

Re-check the scopes of your OAuth app. Ensure that your OAuth application includes all required scopes for the tables you are trying to ingest. See the supported source tables for a complete list of required scopes.

401 Unauthenticated​

Resolution:

Re-authenticate your Unity Catalog connection. Your OAuth credentials might have expired or been revoked.

After authenticating with Jira, you see a "Try Logging In Again" screen​

After authenticating with Jira, you see a "Try Logging In Again" screen, which successfully logs into Jira but never redirects back to Databricks.

Resolution:

  1. Verify the Redirect URI configured in the Jira OAuth app matches the exact workspace redirect path: https://<databricks_workspace_URL>/login/oauth/lakehousefederation.html
  2. Do not click Try Logging In Again. This logs you into the Jira UI instead of redirecting to Databricks. Instead, close the window and restart the OAuth flow from the Databricks UI after fixing the redirect URI.
  3. If the issue persists, confirm that the Jira app has the required scopes: read:jira-work, read:jira-user, plus the granular read scopes listed in Configure Jira for ingestion.

Permission errors​

Error:

Access denied to Jira project or issue.

Resolution:

  1. Confirm that the user account has Browse Projects permission for the projects you are trying to ingest.
  2. Check the project permissions in Jira by navigating to Project settings > Permissions.
  3. If you are using a service account, verify that it has been granted appropriate permissions.
  4. Some issues might have security restrictions. Check individual issue permissions in the Jira interface.

Rate limit errors​

Error:

Jira API rate limit exceeded.

Resolution:

  1. The Jira connector automatically retries with exponential backoff when rate limits are encountered.
  2. If rate limit errors persist, consider scheduling pipeline runs during off-peak hours.
  3. For large Jira instances, you might need to increase the time between pipeline runs.
  4. Contact Atlassian support if you need to increase your API rate limits.

Missing issues or incomplete data​

Issue:

Some issues are not appearing in the ingested data, or the data appears incomplete.

Resolution:

  1. Verify that the issues exist in the source Jira project and are not archived.
  2. Confirm that the user account has access to all the issues in the project.
  3. Check that custom fields are properly configured in your Jira instance.
  4. Check the pipeline event logs for any warnings or errors related to specific issues.

Project not found errors​

Error:

Jira project not found: <PROJECT_KEY>

Resolution:

  1. Verify that the project key is correct. Project keys are case-sensitive.
  2. Check that the project exists and is active (not archived) in your Jira instance.
  3. Confirm that the user account has access to the project.
  4. Try accessing the project directly in your browser: https://your-domain.atlassian.net/browse/<PROJECT_KEY>

Slow ingestion performance​

Issue:

Pipeline runs are taking longer than expected.

Resolution:

  1. Initial pipeline runs (full snapshots) typically take longer than incremental runs.
  2. Projects with extensive workflow history or many custom fields might slow down ingestion.
  3. Check if you are hitting Jira API rate limits by reviewing the pipeline logs.
  4. Consider ingesting specific projects instead of all projects to reduce the data volume.
  5. If performance issues persist, create a support ticket.

OAuth authentication errors​

Issue:

The pipeline was working but suddenly started failing with authentication errors.

Resolution:

  1. The connector automatically refreshes OAuth tokens when they approach expiration. If authentication errors persist, the issue might be related to OAuth app configuration or revocation.
  2. Check that your OAuth app is still active and has not been revoked in the Atlassian Developer Console.
  3. If needed, re-authenticate the Unity Catalog connection by going through the OAuth flow again.
  4. Retry the pipeline.

Column selection using Databricks Asset Bundles​

Issue:

You are unable to use the column selection feature when you create a managed ingestion pipeline using Databricks Asset Bundles.

Resolution:

Check your Databricks CLI version. If the version is below v0.251.0, reinstall the CLI.

Need more help?​

If you encounter an issue that's not covered in this troubleshooting guide, create a support ticket.