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Canopy: An End-to-End Performance Tracing And Analysis System

Authors:

Jonathan Kaldor,

Wiktor Kuropatwa,

Brendan Viscomi,

Vinod Venkataraman,

Kaushik Veeraraghavan,

Yee Jiun SongAuthors Info & Claims

SOSP '17: Proceedings of the 26th Symposium on Operating Systems Principles

Pages 34 - 50

https://doi.org/10.1145/3132747.3132749

Published: 14 October 2017 Publication History

Abstract

This paper presents Canopy, Facebook's end-to-end performance tracing infrastructure. Canopy records causally related performance data across the end-to-end execution path of requests, including from browsers, mobile applications, and backend services. Canopy processes traces in near real-time, derives user-specified features, and outputs to performance datasets that aggregate across billions of requests. Using Canopy, Facebook engineers can query and analyze performance data in real-time. Canopy addresses three challenges we have encountered in scaling performance analysis: supporting the range of execution and performance models used by different components of the Facebook stack; supporting interactive ad-hoc analysis of performance data; and enabling deep customization by users, from sampling traces to extracting and visualizing features. Canopy currently records and processes over 1 billion traces per day. We discuss how Canopy has evolved to apply to a wide range of scenarios, and present case studies of its use in solving various performance challenges.

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cover image ACM Conferences

SOSP '17: Proceedings of the 26th Symposium on Operating Systems Principles

October 2017

677 pages

ISBN:9781450350853

DOI:10.1145/3132747

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