Apollo: towards an efficient distributed orchestration of serverless function compositions in the cloud-edge continuum

Abstract

This paper provides a first presentation of Apollo, an orchestration framework for serverless function compositions distributed across the cloud-edge continuum. Apollo has a modular design that enables a fine-grained decomposition of the runtime orchestration (scheduling, data transmission, etc.) of applications, so that each of the numerous orchestration decisions can be optimized separately, fully exploiting the potential for the optimization of performance and costs. Apollo features (a) a flexible model of the application and the available resources and (b) a decentralized orchestration scheme carried out by independent agents. This flexible structure enables distributing not only the processing but also the orchestration process itself across a large number of resources, each running an independent Apollo instance. In combination with the ability to execute parts of the application directly on the host of each Apollo instance, this unleashes a significant potential for cost and performance optimization by leveraging data locality. Apollo's efficiency and its potential for application performance improvement are demonstrated in a series of experiments---for both synthetic and real function compositions---where Apollo's capability for flexible distribution of tasks between local containers and serverless functions enables a significant application speedup (up to 20X).