Datacenters have traditionally been architected as a collection of servers wherein each server aggregates a fixed amount of computing, memory, storage, and communication resources. In this paper, we advocate an alternative construction in which the resources within a server are disaggregated and the datacenter is instead architected as a collection of standalone resources.Disaggregation brings greater modularity to datacenter infrastructure, allowing operators to optimize their deployments for improved efficiency and performance. However, the key enabling or blocking factor for disaggregation will be the network since communication that was previously contained within a single server now traverses the datacenter fabric. This paper thus explores the question of whether we can build networks that enable disaggregation at datacenter scales.

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By moving network appliance functionality from proprietary hardware to software, Network Function Virtualization promises to bring the advantages of cloud computing to network packet processing. However, the evolution of cloud computing (particularly for data analytics) has greatly benefited from application-independent methods for scaling and placement that achieve high efficiency while relieving programmers of these burdens. NFV has no such general management solutions. In this paper, we present a scalable and application-agnostic scheduling framework for packet processing, and compare its performance to current approaches.