Sonata: query-driven streaming network telemetry

Arpit Gupta, Rob Harrison, Marco Canini, Nick Feamster, Jennifer Rexford, Walter Willinger

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    208 Scopus citations


    Managing and securing networks requires collecting and analyzing network traffic data in real time. Existing telemetry systems do not allow operators to express the range of queries needed to perform management or scale to large traffic volumes and rates. We present Sonata, an expressive and scalable telemetry system that coordinates joint collection and analysis of network traffic. Sonata provides a declarative interface to express queries for a wide range of common telemetry tasks; to enable real-time execution, Sonata partitions each query across the stream processor and the data plane, running as much of the query as it can on the network switch, at line rate. To optimize the use of limited switch memory, Sonata dynamically refines each query to ensure that available resources focus only on traffic that satisfies the query. Our evaluation shows that Sonata can support a wide range of telemetry tasks while reducing the workload for the stream processor by as much as seven orders of magnitude compared to existing telemetry systems.
    Original languageEnglish (US)
    Title of host publicationProceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication - SIGCOMM '18
    PublisherAssociation for Computing Machinery (ACM)
    Number of pages15
    ISBN (Print)9781450355674
    StatePublished - Aug 8 2018

    Bibliographical note

    KAUST Repository Item: Exported on 2020-10-01
    Acknowledgements: We thank our shepherd (Ion Stoica), Rüdiger Birkner, Ankita Pawar, Mina T. Arashloo, Robert MacDavid, Chris Mac-Stoker, Rachit Agarwal, and the anonymous reviewers for the feedback and comments. This research was supported by NSF Awards CNS-1539902 and CNS-1704077. Jennifer Rexford was additionally supported by gifts from Intel and Huawei.


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