Google Research

Omega: flexible, scalable schedulers for large compute clusters

  • Malte Schwarzkopf
  • Andy Konwinski
  • Michael Abd-El-Malek
  • John Wilkes
SIGOPS European Conference on Computer Systems (EuroSys), ACM, Prague, Czech Republic (2013), pp. 351-364

Abstract

Increasing scale and the need for rapid response to changing requirements are hard to meet with current monolithic cluster scheduler architectures. This restricts the rate at which new features can be deployed, decreases efficiency and utilization, and will eventually limit cluster growth. We present a novel approach to address these needs using parallelism, shared state, and lock-free optimistic concurrency control.

We compare this approach to existing cluster scheduler designs, evaluate how much interference between schedulers occurs and how much it matters in practice, present some techniques to alleviate it, and finally discuss a use case highlighting the advantages of our approach -- all driven by real-life Google production workloads.

Learn more about how we do research

We maintain a portfolio of research projects, providing individuals and teams the freedom to emphasize specific types of work