What factors would you consider before deploying an LLM into production?

I am preparing for Generative AI and Machine Learning interviews and would like to understand the key considerations before deploying a Large Language Model (LLM) into a production environment.

Could someone explain:

How should I evaluate the model's accuracy, latency, scalability, and cost?
What security and privacy measures should be implemented to protect sensitive user data?
How can I reduce hallucinations and improve response reliability using techniques such as Retrieval-Augmented Generation (RAG), guardrails, or prompt engineering?
What monitoring and logging practices should be used to track model performance, errors, and user feedback after deployment?
How should I handle API rate limits, fallback mechanisms, versioning, and model updates?
What are the best practices for testing an LLM before releasing it to production?
Could you provide a real-world architecture or deployment workflow for an LLM-powered application?