Hi @qsuser
When managing Quick Sight dashboards across environments for example, migrating dashboards from development to production or backing them up it’s important to note how Quick Sight’s APIs handle dashboard definitions.
Unlike the Quick Sight console, which allows you to create or publish dashboards even if there are some issues like missing fields or invalid calculated columns, the API operations (such as describe-dashboard-definition and create-dashboard) enforce stricter validation. This means that if your dashboard JSON contains invalid calculated fields, references to missing dataset columns, or unsupported formatting options, the API calls will fail with errors like INVALID_CALCULATED_COLUMN_EXPRESSION or INVALID_CONDITIONAL_FORMATTING_EXPRESSION. As a result, directly exporting and recreating dashboards using these API commands may be challenging when dashboards have evolved or datasets have changed.
To address this, AWS strongly recommends using Quick Sight templates for backup and migration workflows. Templates provide an abstraction layer that allows easier migration by decoupling dashboards from specific dataset details and mitigating errors caused by missing or renamed fields. Using templates, you can export the core dashboard and analysis logic, update dataset mappings, and then deploy dashboards in new environments more reliably.
- Validate and clean up your dashboards and analyses in the source environment to remove or fix invalid calculated fields or broken references before exporting.
- Use the API commands to create templates from your existing analyses or dashboards.
- Deploy dashboards in the target environment from these templates by mapping datasets accordingly.
Please refer to the below Quick Sight documentations and community post this might be helpful for you.