LAB-003 / Infrastructure
Architecture guideProduction AI Application Architecture
A reference deployment path for secure, observable AI inference services.
Architecture flow
01Client/API
02Auth + policy
03Inference service
04Model gateway
05Telemetry
A conceptual serving path. Production platforms also require secret management, lifecycle controls, rollout strategy and recovery design.
Control plane
Manage images, model definitions, configuration and policy through versioned delivery pipelines. Prefer repeatable infrastructure and explicit approvals for sensitive changes.
Data plane
Authenticate requests, apply policy, route inference traffic and use quotas, timeouts, retries and backpressure to protect shared resources.
Operations
Monitor availability, latency, tokens, cost, quality, safety signals and model drift. Design rollback and incident-response paths before promoting releases.
This is an architecture guide, not a deployed application or runnable reference implementation. Further source code and guided exercises will be added after validation.