How to Add AI Gateway Observability to a Production Control Plane
A lot of teams add an AI gateway for a good reason. They want one place to enforce policy. They want one place to shape traffic. They want one place to introduce retries, failover, quotas, and mode...

Source: DEV Community
A lot of teams add an AI gateway for a good reason. They want one place to enforce policy. They want one place to shape traffic. They want one place to introduce retries, failover, quotas, and model controls without rewriting every application. That architecture makes sense. But once the gateway starts making real decisions, it is no longer just a proxy. It becomes part of the production control plane. That is the point where AI gateway observability matters. Why a gateway becomes hard to debug In a direct-to-provider setup, the debugging path is smaller. You usually inspect: the application request the provider call the final response A gateway inserts a new decision layer in the middle. Now the same request may go through: a policy check a quota or budget guardrail route selection logic a retry branch a failover path a downstream provider call response shaping before it returns to the app If latency spikes or the wrong provider is used, the real problem may not be the downstream mode