How would you implement a "Token Quota" system to prevent a single user or a bug in your code from spending $1,000 on API calls in an hour?

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

How do you track which specific feature or user in your app is driving the most "Token Spend"?

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?