How do you monitor for "Concept Drift" in an LLM application? If the model's output starts getting shorter over time, is that a deployment failure or a data failure?

Explain how Continuous Batching (used in engines like vLLM) differs from traditional static batching. How does it improve GPU utilization?

If you have 100 different customers, each with a custom-tuned LoRA adapter, do you need 100 different GPU clusters? How would you serve them efficiently on one cluster?

What constitutes a "Health Check" for an AI model? Is checking if the HTTP port is open enough?