Toward Scientific Workflows in a Serverless World

Abstract

Serverless computing and FaaS have gained popularity due to their ease of design, deployment, scaling and billing on clouds. However, when used to compose and orchestrate scientific workflows, they pose limitations due to cold starts, message indirection, vendor lock-in and lack of provenance support. Here, we propose a design for a Ser verless Scientific Workflow Orchestrator that overcomes these challenges using techniques like function fusion, pilot invocations and data fabrics.