How do you design a scalable Keras training pipeline for production systems?

A scalable Keras pipeline separates data ingestion, training, evaluation, and deployment into modular components.

Production pipelines use tf.data for input efficiency, distributed training strategies for scaling, checkpointing for fault tolerance, and containerized environments for reproducibility. Each stage is decoupled to allow independent scaling and monitoring.