Reliability Architecture for Distributed Edge AI Systems
Executive Summary
Distributed inference moves decision-making closer to operational systems, but it also introduces new reliability constraints across connectivity, orchestration, model versioning, and device-level compute.
A resilient architecture therefore needs one central control layer coordinated control with local fail-safe behaviour, supported by observable service boundaries and defined recovery paths.
Evidence & Design Considerations
Failure analysis should distinguish between network isolation, model drift, resource saturation, and policy inconsistency so mitigation decisions can be matched to the actual failure mode.