Re-embedding workflow causes service disruption and cascading delays

When a dataset must be re-embedded due to an embedding model upgrade, stopping workflows to perform the re-embedding leads to cascading delays in ongoing projects. At multi-million-document scale, re-embedding can be time-consuming and resource-intensive, increasing operational costs and causing workflow interruptions.

Run old and new embedding model pipelines in parallel to avoid downtime. Use collection aliases to reference the active collection by alias name; when the new collection with updated embeddings is ready, update the alias pointer for instant cutover with no application changes. This allows zero-downtime transitions and instant rollback capability.