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Invisinets: Removing Networking from Cloud Networks

Sarah McClure, Zeke Medley, Deepak Bansal, Karthick Jayaraman, Ashok Narayanan, Jitendra Padhye, Sylvia Ratnasamy, Anees Shaikh, Rishabh Tewari

2023Year

Abstract

Cloud tenant networks are complex to provision, configure, and manage. Tenants must figure out how to assemble, configure, test, etc. a large set of low-level building blocks in order to achieve their high-level goals. As these networks are increasingly spanning multiple clouds and on-premises infrastructure, the complexity scales poorly. We argue that the current cloud abstractions place an unnecessary burden on the tenant to become a seasoned network operator. We thus propose an alternative interface to the cloud provider's network resources in which a tenant's connectivity needs are reduced to a set of parameters associated with compute endpoints. Our API removes the tenant networking layer of cloud deployments altogether, placing its former duties primarily upon the cloud provider. We demonstrate that this API reduces the complexity experienced by tenants by 80-90% while maintaining a scalable and secure architecture. We provide a prototype of the underlying infrastructure changes necessary to support new functionality introduced by our interface and implement our API on top of current cloud APIs.

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