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Various Edge nodes are often not interconnected and the direct inter-communication of traffic between applications on these edge nodes is highly desirable requirement for businesses. EdgeMesh addresses these challenges by shielding the complex network topology at the edge applications scenario. The following is a architecture diagram for Karmada. More details related to EdgeMesh project can be found here.
- Service Discovery: Retrieves the endpoint address of the edge cloud service instance depending on the UE location, network conditions, signal strength, delay, App QoS requirements etc.
- Mobility Management: Cloud Core side mobility service subscribes to UE location tracking events or resource rebalancing scenario. Upon UE mobility or resource rebalancing scenario, mobility service uses Cloud core side Service Discovery service interface to retrieve the address of new appropriate location-aware edge node. Cloud Core side mobility service subsequently initiates UE application state migration process between edge nodes. Simple CRIU container migration strategy may not be enough, much more complex than VM migration.
- Multi-Access Gateway: Multi access gateway controller manages Edge Data Gateway and Access APIG of edge nodes. Edge data gateway connects with edge gateway (UPF) of 5g network system, and routes traffic to containers on edge nodes. Access APIG connects with the management plane of 5g network system (such as CAPIF), and pulls QoS, RNIS, location and other capabilities into the edge platform.
- AutoScaling: Autoscaler provides capability to automatically scale the number of Pods (workloads) based on observed CPU utilization (or on some other application-provided metrics). Autoscaler also provides vertical Pod autoscaling capability by adjusting a container’s ”CPU limits” and ”memory limits” in accordance to the autoscaling policies.
- Service Catalog: It provides a way to list, provision, and bind with services without needing detailed knowledge about how those services are created or managed.
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