Orchestrating the Execution of Serverless Functions in Hybrid Clouds

TL;DR

This paper introduces a Hybrid Cloud Scheduler that orchestrates serverless batch-processing pipelines across heterogeneous infrastructures, improving deadline adherence and reducing costs.

Contribution

It presents a novel scheduler framework for executing serverless batch pipelines over hybrid clouds, enhancing efficiency and deadline compliance.

Findings

Improved deadline meeting probability for batch pipelines.

Cost reduction through private resource utilization.

Effective orchestration across heterogeneous infrastructures.

Abstract

In recent years, serverless computing, especially Function as a Service (FaaS), is rapidly growing in popularity as a cloud programming model. The serverless computing model provides an intuitive interface for developing cloud-based applications, where the development and deployment of scalable microservices has become easier and cost-effective. An increasing number of batch-processing applications are deployed as pipelines that comprise a sequence of functions that must meet their deadline targets to be practical. In this paper, we present our Hybrid Cloud Scheduler (HCS) for orchestrating the execution of serverless batch-processing pipelines deployed over heterogeneous infrastructures. Our framework enables developers to (i) automatically schedule and execute batch-processing applications in heterogeneous environments such as the private edge and public cloud serverless infrastructures, (ii) benefit from cost reduction through the utilization of their own resources in a private cluster, and (iii) significantly improves the probability of meeting the deadline requirements of their applications. Our experimental evaluation demonstrates the efficiency and benefits of our approach.