Enterprise MLOps: Continuous Integration and Model Serving at Scale

Transitioning models from research notebooks to live production systems requires robust MLOps orchestration. This guide reviews Docker containerization, Kubernetes scaling, real-time feature stores, model monitoring pipelines, and high-throughput execution engines like Triton Inference Server and TensorRT optimization.