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High-Availability at Massive Scale: Building Google’s Data Infrastructure for Ads

  • Ashish GuptaEmail author
  • Jeff ShuteEmail author
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 337)

Abstract

Google’s Ads Data Infrastructure systems run the multi-billion dollar ads business at Google. High availability and strong consistency are critical for these systems. While most distributed systems handle machine-level failures well, handling datacenter-level failures is less common. In our experience, handling datacenter-level failures is critical for running true high availability systems. Most of our systems (e.g. Photon, F1, Mesa) now support multi-homing as a fundamental design property. Multi-homed systems run live in multiple datacenters all the time, adaptively moving load between datacenters, with the ability to handle outages of any scale completely transparently.

This paper focuses primarily on stream processing systems, and describes our general approaches for building high availability multi-homed systems, discusses common challenges and solutions, and shares what we have learned in building and running these large-scale systems for over ten years.

Keywords

Stream processing Distributed systems Multi-homing Databases 

Notes

Acknowledgements

We would like to thank the teams inside Google who built and ran the systems we have described, and the earlier generations of systems that informed our current designs. We would like to thank Divyakant Agrawal for his help preparing this paper.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Google Inc.Mountain ViewUSA

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