Topology-aware Serverless Function-Execution Scheduling

TL;DR

This paper introduces tAPP, a declarative language for topology-aware serverless function scheduling, enabling constraints to be enforced without platform modifications, demonstrated through an extension of Apache OpenWhisk.

Contribution

The paper presents tAPP, a novel declarative language for topology-aware scheduling, and implements it in an extension of Apache OpenWhisk to support constrained function placement.

Findings

Supports multiple topological constraints simultaneously

Does not degrade performance for unconstrained scenarios

Improves performance for topology-bound applications

Abstract

Cloud-edge serverless applications or serverless deployments spanning multiple regions introduce the need to govern the scheduling of functions to satisfy their functional constraints or avoid performance degradation. For instance, functions may require to be allocated to specific private (edge) nodes that have access to specialised resources or to nodes with low latency to access a certain database to decrease the overall latency of the application. State-of-the-art serverless platforms do not support directly the implementation of topological constraints on the scheduling of functions. We address this problem by presenting a declarative language for defining topology-aware, function-specific serverless scheduling policies, called tAPP. Given a tAPP script, a compatible serverless scheduler can enforce different, co-existing topological constraints without requiring ad-hoc platform deployments. We prove our approach feasible by implementing a tAPP-based serverless platform as an extension of the Apache OpenWhisk serverless platform. We show that, compared to vanilla OpenWhisk, our extension does not negatively impact the performance of generic, non-topology-bound serverless scenarios, while it increases the performance of topology-bound ones.