Session
Building An Elastic, Scalable Cloud-Native Digital Twin by Leveraging Stream Adaptation Agents
Industrial digital twins operating across geographically distributed manufacturing facilities must simultaneously contend with concept drift, workload surges, and infrastructure failures, conditions that expose a fundamental gap in static, periodically retrained architectures: they treat adaptation, resource provisioning, and resilience as independent, offline concerns rather than as jointly managed
operational properties. This paper addresses that gap with a cloud-native systems architecture that closes the adaptation-provisioning resilience control loop in a single, continuously operating coordination plane. The architecture integrates four tightly coupled infrastructure mechanisms: stream-resident Stream Adaptation Agents (SAA) that perform partition-level drift monitoring and quorum gated orchestration; a Shared Adaptive Inference Layer that maintains a streaming ensemble model updated in-place without service interruption.
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