Google Research

Geo-Distribution of Actor-Based Services

  • Philip A. Bernstein
  • Sebastian Burckhardt
  • Sergey Bykov
  • Natacha Crooks
  • Jose Faleiro
  • Gabriel Kliot
  • Alok Kumbhare
  • Muntasir Raihan Rahman
  • Vivek Shah
  • Adriana Szekeres
  • Jorgen Thelin
Proc. of ACM Programming Languages, OOPSLA (2017)


Many service applications use actors as a programming model for the middle tier, to simplify synchronization, fault-tolerance, and scalability. However, efficient operation of such actors in multiple, geographically distant datacenters is challenging, due to the very high communication latency. Caching and replication are essential to hide latency and exploit locality; but it is not a priori clear how to combine these techniques with the actor programming model. We present Geo, an open-source geo-distributed actor system that improves performance by caching actor states in one or more datacenters, yet guarantees the existence of a single latest version by virtue of a distributed cache coherence protocol. Geo’s programming model supports both volatile and persistent actors, and supports updates with a choice of linearizable and eventual consistency. Our evaluation on several workloads shows substantial performance benefits, and confirms the advantage of supporting both replicated and single-instance coherence protocols as configuration choices. For example, replication can provide fast, always-available reads and updates globally, while batching of linearizable storage accesses at a single location can boost the throughput of an order processing workload by 7x.

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