Model Serving and Latency Considerations Questions

Cover practical design choices for serving models in production under latency and throughput constraints. Discuss batch versus real time inference, techniques to reduce latency such as model compression, quantization and distillation, caching and precomputation of features, batching strategies, multi model serving, autoscaling and capacity planning, and tradeoffs between model complexity and operational cost. Include monitoring of service level objectives and graceful degradation approaches.