Practical Cloud Workloads for Serverless FaaS

Abstract

Serverless computing is gaining popularity with the Function-asa-Service (FaaS) execution model. Without incurring overheads involved in provisioning cloud instances and with high availability and scalability, serverless computing allows developers to focus on implementation of core application logic using other well-developed cloud services. By abstracting the complex resource management task, serverless computing opens new opportunities for the cloud service adoption even to non-cloud experts [2]. With the popularity, many research results have been published using the FaaS execution model. They include investigation of serverless computing opportunities [1], proposing new serverless applications, function run-time optimization, and public service comparison. Without a common test benchmark suite, authors in the previous work had evaluated proposed systems using fairly simple FaaS applications, such as micro-benchmarks that emphasize specific resources exclusively, e.g., CPU, disk I/O, and network. However, such simple workloads do not represent realistic FaaS system applications, and the evaluations might not compare proposed systems appropriately.