Real Time Inference and Serving Constraints Questions

Design and engineering considerations for serving models with strict latency and availability requirements. Topics include understanding latency budgets and service level objectives, choosing between batch and real time inference, synchronous versus asynchronous patterns, request batching, caching strategies, model warm start and cold start handling, graceful degradation and fallback policies, model optimization techniques such as quantization and pruning, trade offs between model complexity and inference cost, state and consistency management for online features, back pressure and queueing strategies, deployment orchestration, and operational monitoring and alerting for inference pipelines.