How does TensorFlow handle model version rollback in production?

Model rollback is handled using versioned deployments in TensorFlow Serving.

TensorFlow Serving supports multiple model versions simultaneously. If a new version degrades performance, traffic can be routed back to a previous stable version. This ensures zero-downtime rollback and safe deployment strategies.