In addition to this: I’d also recommend having some sort of fallback strategy. Sometimes a model is completely off but the other ones are working seamlessly. Retrying the same model over and over will not help, but falling back to a different (usually worse) model will do.
In my case, a generic service checks out the model’s health by pinging them every minute, and updates this models’ health in a database. When any of the other services want to call OpenAI’s API using a particular model, they firstly retrieve the model’s health from the database. If it’s ok, they call it with a retry mechanism. If not, they call the best one available at that precise moment (also with a retry mechanism).