Vigil: Effective End-to-end Monitoring for Large-scale Recommender Systems at Glance
Pages 5249 - 5250
Abstract
The success of large-scale recommender systems hinges upon their ability to deliver accurate and timely recommendations to a diverse user base. At Glance, we deliver snackable personalized content to the lock screens of 200M smartphones. In this context, continuous monitoring is paramount as it safeguards data integrity, detects drifts, addresses evolving user preferences, optimizes system downtime, and ultimately augments the system's effectiveness and user satisfaction. In this talk, we delve into Vigil, a set of monitoring practices developed to provide comprehensive end-to-end monitoring of recommender systems at Glance. These practices revolve around three key pillars: mitigating developer fatigue, ensuring precise predictions, and establishing a centralized monitoring framework. By adopting these practices, we have observed a 30% reduction in compute cost, a 26% drop in downtime, and a surge in developer productivity demonstrated by a 45% decrease in turnaround time.
References
[1]
David Nigenda, Zohar Karnin, Muhammad Bilal Zafar, Raghu Ramesha, Alan Tan, Michele Donini, and Krishnaram Kenthapadi. 2021. Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models. arXiv preprint arXiv:2111.13657 (2021).
[2]
Mohammad Saberian and Justin Basilico. 2021. RecSysOps: Best Practices for Operating a Large-Scale Recommender System. In Proceedings of the 15th ACM Conference on Recommender Systems. 590--591.
[3]
Prashanth Thinakaran, Kanak Mahadik, Jashwant Gunasekaran, Mahmut Taylan Kandemir, and Chita R Das. 2022. SandPiper: A Cost-Efficient Adaptive Framework for Online Recommender Systems. In 2022 IEEE International Conference on Big Data. IEEE.
Index Terms
- Vigil: Effective End-to-end Monitoring for Large-scale Recommender Systems at Glance
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Information & Contributors
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Published In
October 2023
5508 pages
ISBN:9798400701245
DOI:10.1145/3583780
- General Chairs:
- Ingo Frommholz,
- Frank Hopfgartner,
- Mark Lee,
- Michael Oakes,
- Program Chairs:
- Mounia Lalmas,
- Min Zhang,
- Rodrygo Santos
Copyright © 2023 Owner/Author.
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Association for Computing Machinery
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Published: 21 October 2023
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CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management
October 21 - 25, 2023
Birmingham, United Kingdom
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