Post-Upgrade Issues and Version Compatibility

After upgrading DataHub to a new version, previously working functionality breaks, features disappear, or new errors appear. This includes ingestion source failures, UI component issues, and API compatibility problems.

Common Error Messages:

• ModuleNotFoundError: No module named 'datahub.metadata._schema_classes'
• Version mismatch between executor and server
• Ingestion jobs stuck in Pending state

Note: For DataHub Cloud customers, infrastructure-level changes (Kubernetes, AWS resources, operating system configurations) are managed by DataHub Support. The solutions below focus on configuration changes that customers can implement.

1. Check compatibility after upgrade:

   • Review release notes for breaking changes in the new version
   • Verify CLI version matches the server version
   • Update ingestion recipe syntax if deprecated options were used

2. Common post-upgrade issues:

   • UI features disappear: Check if feature flags changed
   • Ingestion sources fail: Update recipe configuration to new format
   • API errors: Review GraphQL schema changes
   • SQL assertions not visible: Feature may require re-enabling

3. Update CLI and dependencies:

pip install --upgrade 'acryl-datahub[all]'
datahub version  # Verify version matches server

4. Reconfigure ingestion after upgrade:

   • Some executors may need recreation after major version upgrades
   • Review executor status in UI: Settings → Integrations → Ingestion Sources
   • Delete and recreate affected ingestion sources if needed

5. Contact support for cloud instances:

   • DataHub Support handles infrastructure upgrades for cloud customers
   • Report unexpected behavior immediately after upgrade
   • Request rollback if critical functionality is broken

Always backup your DataHub configuration before making changes. Test solutions in a non-production environment when possible.

Related Tickets: - 5829, 5534, 5936, 5919, 5886, 5852, 5847, 5839

• 5829, 5534, 5936, 5919, 5886, 5852, 5847, 5839