Why Agent Infrastructure Is Its Own Discipline

Platform engineers often treat AI agents like standard stateless microservices, containerizing them and deploying them with traditional Kubernetes configurations. However, this approach frequently fails in production because agent requests differ fundamentally from standard HTTP requests. Agents involve long-running reasoning chains, variable compute loads, and stateful interactions that break common assumptions about liveness probes, autoscaling, and session management. For instance, standard liveness probes often kill agents mid-reasoning, while CPU-based autoscaling fails to track actual workload demands. The article argues that agent infrastructure requires a distinct architectural approach, emphasizing the separation of process health from forward progress and the use of explicit state handling rather than pinned sessions. By moving away from the 'stateless service' playbook, teams can avoid silent failures and improve the reliability of their agent deployments.