Monitoring Large Language Models (LLMs) is crucial for maintaining their performance, reliability, and safety in production environments. Inadequate monitoring can lead to significant financial losses and damage a company's reputation due to inaccurate or inappropriate AI outputs. Effective monitoring helps maintain system health, improves model outputs, and ensures compliance with regulatory standards. It involves tracking specific metrics that reflect performance and resource usage at scale, addressing LLM evaluation challenges. Monitoring also aims to detect anomalies like hallucinations, prevent harmful or biased content, and ensure models follow ethical guidelines. By leveraging advanced monitoring tools, organizations can reduce unintended biases, prevent misuse, and build trust with users and stakeholders.