How would you manage schema evolution while implementing CDC?

Managing schema evolution while implementing CDC requires a combination of versioned schemas, compatibility checks, and automated pipeline adjustments. First, store every schema change in a registry and define compatibility rules (backward, forward, full). Tools like Debezium or AWS DMS can capture row‑level changes, but they need to understand the current schema. When a new column is added, the CDC connector can emit nulls for existing rows; when a column is removed, you must decide whether to drop it or keep it for historical data. Use a schema evolution policy that automatically updates the target table or triggers a migration script. Continuous integration tests should compare the source and target schemas after each change. If a breaking change is detected, the pipeline can pause, alert the team, and apply a migration. This approach keeps the CDC pipeline robust against schema drift.