LLMOps (Large Language Model Operations) is the specialized discipline of deploying, managing, monitoring, and maintaining large language models in production environments. It extends traditional MLOps practices while addressing unique challenges of LLMs, including prompt engineering, inference optimization, hallucination detection, and massive computational requirements. Unlike classic ML pipelines, LLMOps must handle non-deterministic outputs, context window constraints, costly API calls, and the rapid evolution of model capabilities—making observability, cost control, and iterative experimentation central to every deployment.

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