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  • Edge Computing: With business logic running at the Edge, much larger volumes of data can be secured & processed locally where the data is produced. Edge nodes can run autonomously which effectively reduces the network bandwidth requirements and consumptions between Edge and Cloud. With data processed at the Edge, the responsiveness is increased dramatically and data privacy is protected.

  • Simple App. Development: Developers can write regular http or mqtt based applications, containerize them, verify at cloud and port to edge without worry.

  • Cloud Native: With KubeEdge, users can orchestrate apps, manage devices and monitor app and device status on Edge nodes just like a traditional Kubernetes cluster in the Cloud. Locations of edge nodes are transparent to customers.

  • Extensible Infra. for IOT/Edge: Based on Kubernetes, KubeEdge is highly extensible. Currently using MQTT broker and device twin at edge, KubeEdge can enable customers enable IOT functionalities. As listed above, KubeEdge architecture also addressed the key technical challenges specific for IOT/Edge workload.

  • Light weight agent: Currently the agent memory footprint is about 10MB 70MB at runtime. With it, the edge side hardware can be Rasberri-pi or large server

  • Compatible to K8s APIs:Currently support K8s core API versions from 1.12 - 1.18 .