Opening Up Black Box Networks with CloudTalk

Optimizing distributed applications in the cloud requires network topology information, yet this information is kept confidential by the cloud providers. Today, applications can infer network properties and optimize accordingly but this is costly to get right. The cloud can optimize the network via load balancing, but the scope is limited to moving traffic between the available paths.

In this paper we challenge this status quo. We show that network topology information is not confidential in the first place by conducting a study of Amazon’s EC2 topology, and we show how such information can have a big impact in optimizing a web search application.

We propose that applications and the network should break the silence and communicate to allow better optimizations that will benefit both parties. To this end we design CloudTalk, a very simple language that allows apps to express traffic patterns that are then ranked by the network. The ranking helps application pick the right way to implement its tasks. We provide a proof-of-concept implementation of CloudTalk showing that it is expressive enough to capture many traffic patterns and that it is feasible to use in practice.