Owl: Scale and Flexibility in Distribution of Hot Content


Jason Flinn, Xianzheng Dou, Arushi Aggarwal, Alex Boyko, Francois Richard, Eric Sun, Wendy Tobagus, Nick Wolchko, and Fang Zhou, Meta


Owl provides high-fanout distribution of large data objects to hosts in Meta’s private cloud. Owl combines a decentralized data plane based on ephemeral peer-to-peer distribution trees with a centralized control plane in which tracker services maintain detailed metadata about peers, their cache state, and ongoing downloads. In Owl, peer nodes are simple state machines and centralized trackers decide from where each peer should fetch data, how they should retry on failure, and which data they should cache and evict. Owl trackers provide a highly-flexible and configurable policy interface that customizes and optimizes behavior for widely-varying distribution use cases. In contrast to prior assumptions about peer-to-peer distribution, Owl shows that centralizing the control plan is not a barrier to scalability: Owl distributes over 800 petabytes of data per day to millions of client processes. Owl improves download speeds by a factor of 2–3 over both BitTorrent and a prior decentralized static distribution tree used at Meta, while supporting 106 use cases which collectively employ 55 different distribution policies.

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@inproceedings {280908,
author = {Jason Flinn and Xianzheng Dou and Arushi Aggarwal and Alex Boyko and Francois Richard and Eric Sun and Wendy Tobagus and Nick Wolchko and Fang Zhou},
title = {Owl: Scale and Flexibility in Distribution of Hot Content},
booktitle = {16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22)},
year = {2022},
isbn = {978-1-939133-28-1},
address = {Carlsbad, CA},
pages = {1--15},
url = {https://www.usenix.org/conference/osdi22/presentation/flinn},
publisher = {USENIX Association},
month = jul

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