Stormy: an elastic and highly available streaming service in the cloud

  • Authors:
  • Simon Loesing;Martin Hentschel;Tim Kraska;Donald Kossmann

  • Affiliations:
  • Systems Group, ETH Zurich;Systems Group, ETH Zurich;University of California, Berkeley;Systems Group, ETH Zurich

  • Venue:
  • Proceedings of the 2012 Joint EDBT/ICDT Workshops
  • Year:
  • 2012

Quantified Score

Hi-index 0.00

Visualization

Abstract

In recent years, new highly scalable storage systems have significantly contributed to the success of Cloud Computing. Systems like Dynamo or Bigtable have underpinned their ability to handle tremendous amounts of data and scale to a very large number of nodes. Although these systems are designed the store data, the fundamental architectural properties and the techniques used (e.g., request routing, replication and load balancing) can also be applied to data streaming systems. In this paper, we present Stormy, a distributed stream processing service for continuous data processing. Stormy is based on proven techniques from existing Cloud storage systems that are adapted to efficiently execute streaming workloads. The primary design focus lies in providing a scalable, elastic, and fault-tolerant framework for continuous data processing, while at the same time optimizing resource utilization and increasing cost efficiency. Stormy is able to process any kind of streaming workloads, thus, covering a wide range of use cases ranging from realtime data analytics to long-term data aggregation jobs.