How do TensorFlow systems isolate faulty model versions in production?

They isolate models using versioned deployment, traffic segmentation, and circuit breakers.

Faulty model versions can be isolated using traffic splitting, where only a subset of requests are routed to new versions. Circuit breakers stop traffic when error thresholds are exceeded. TensorFlow Serving supports multiple model versions concurrently, allowing isolation and rollback without system downtime.