AI Gateway Selection and Implementation: Choosing the Right Pattern for Enterprise AI

This article provides a comprehensive decision framework for choosing the right AI gateway pattern in enterprise environments. It emphasizes that there is no one-size-fits-all solution and that the choice depends on the primary control problem: API governance, model routing/caching/token visibility, agent tool access, or platform engineering needs. It compares traditional API management platforms, edge AI gateways, LLM proxies, Kubernetes-native gateways, and agent tool gateways, highlighting their strengths and weaknesses. The article advises starting small with one route and scaling after validating the operating model, covering aspects like telemetry, budget controls, fallback testing, and rollback. It is a technical guide aimed at IT professionals and architects involved in AI infrastructure decisions.