This article explores LLMOps, detailing its challenges and best practices for managing Large Language Models (LLMs) in production. It compared LLMOps with traditional MLOps, covering hardware needs, performance metrics, and handling non-deterministic outputs. The guide outlines steps for deploying LLMs, including model selection, fine-tuning, and continuous monitoring, while emphasizing quality and security management.