Edge computing brings cloud services closer to the edge of the network, where data originates, and dramatically reduces the network latency of the cloud. It is a bridge linking clouds and users making the foundation for novel interconnected applications. However, edge computing still faces many challenges like remote configuration, well-defined native applications model, and limited node capacity. It lacks geo-organization and a clear separation of concerns. As such edge computing is hard to be offered as a service for future real-time user-centric applications. This paper presents the dynamic organization of geodistributed edge nodes into micro data-centers to cover any arbitrary area and expand capacity, availability, and reliability. A cloud organization is used as an influence with adaptations for a different environment, and a model for edge applications utilizing these adaptations is presented. It is argued that the presented model can be integrated into existing solutions or used as a base for the development of future systems. Furthermore, a clear separation of concerns is given for the proposed model. With the separation of concerns setup, edge-native applications model, and a unified node organization, we are moving towards the idea of edge computing as a service, like any other utility in cloud computing.INDEX TERMS cloud computing, distributed systems, edge computing, formal specifications, infrastructure as software, platform

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Edge computing offers cloud services closer to data sources and end-users, making the foundation for novel applications. The infrastructure deployment is taking off, bringing new challenges: how to use geo-distribution properly, or harness the advantages of having resources at a specific location? New real-time applications require multi-tier infrastructure, preferably doing data preprocessing locally, but using the cloud for heavy workloads. We present a model, able to organize geo-distributed nodes into micro clouds dynamically, allowing resource reorganization to best serve population needs. Such elasticity is achieved by relying on cloud organization principles, adapted for a different environment. The desired state is specified descriptively, and the system handles the rest. As such, infrastructure is abstracted to the software level, thus enabling “infrastructure as software” at the edge. We argue about blending the proposed model into existing tools, allowing cloud providers to offer future micro clouds as a service.