MLOps

MLOps (Machine Learning Operations) is the set of practices that operationalize ML and AI models in production — covering CI/CD pipelines for model updates, automated testing, performance monitoring, data versioning, and rollback procedures. MLOps applies to both traditional ML models and LLM-based systems.

LLMOps is the LLM-specific extension of MLOps, addressing prompt versioning, output evaluation pipelines, safety testing, and the management of retrieval infrastructure. Organizations shipping AI without MLOps practices accumulate silent model debt that surfaces as mysterious accuracy degradation.