ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2111.07226
23
13

Practical Scheduling for Real-World Serverless Computing

14 November 2021
Kostis Kaffes
N. Yadwadkar
Christos Kozyrakis
ArXivPDFHTML
Abstract

Serverless computing has seen rapid growth due to the ease-of-use and cost-efficiency it provides. However, function scheduling, a critical component of serverless systems, has been overlooked. In this paper, we take a first-principles approach toward designing a scheduler that caters to the unique characteristics of serverless functions as seen in real-world deployments. We first create a taxonomy of scheduling policies along three dimensions. Next, we use simulation to explore the scheduling policy space for the function characteristics in a 14-day trace of Azure functions and conclude that frequently used features such as late binding and random load balancing are sub-optimal for common execution time distributions and load ranges. We use these insights to design Hermes, a scheduler for serverless functions with three key characteristics. First, to avoid head-of-line blocking due to high function execution time variability, Hermes uses a combination of early binding and processor sharing for scheduling at individual worker machines. Second, Hermes uses a hybrid load balancing approach that improves consolidation at low load while employing least-loaded balancing at high load to retain high performance. Third, Hermes is both load and locality-aware, reducing the number of cold starts compared to pure load-based policies. We implement Hermes for Apache OpenWhisk and demonstrate that, for the case of the function patterns observed both in the Azure and in other real-world traces, it achieves up to 85% lower function slowdown and 60% higher throughput compared to existing policies.

View on arXiv
Comments on this paper