analiza aiqbench

Yelp's new Training Orchestrator addresses critical scalability challenges in large-scale machine learning by replacing fragmented Spark scripts with a unified, DAG-based execution model. This configuration-driven approach decouples pipeline logic from infrastructure details, enabling reproducible local testing and consistent production runs without sacrificing flexibility. For enterprise ML operations, this shift toward standardized orchestration reduces technical debt while improving the reliability of training pipelines across diverse environments.