Demonstration Paper: Monitoring Machine Learning Contracts with QoA4ML

Tri Nguyen; Linh Truong

doi:10.1145/3447545.3451172

Demonstration Paper: Monitoring Machine Learning Contracts with QoA4ML

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

Abstract

Using machine learning (ML) services, both service customers and providers need to monitor complex contractual constraints of ML service that are strongly related to ML models and data. Therefore, establishing and monitoring comprehensive ML contracts are crucial in ML serving. This paper demonstrates a set of features and utilities of the QoA4ML framework for ML contracts.

Original language	English
Title of host publication	Companion of the 2021 ACM/SPEC International Conference on Performance Engineering (ICPE ’21 Companion), April 19–23, 2021, France
Number of pages	2
DOIs	https://doi.org/10.1145/3447545.3451172
Publication status	Accepted/In press - 19 Apr 2021
MoE publication type	A4 Article in a conference publication
Event	ACM/SPEC International Conference on Performance Engineering - Virtual, Online, Rennes, France Duration: 19 Apr 2021 → 23 Apr 2021

Conference

Conference	ACM/SPEC International Conference on Performance Engineering
Abbreviated title	ICPE
Country	France
City	Rennes
Period	19/04/2021 → 23/04/2021

Keywords

Service contract
ML Serving,
SLO/SLA
System monitoring

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Cite this

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title = "Demonstration Paper: Monitoring Machine Learning Contracts with QoA4ML",

abstract = "Using machine learning (ML) services, both service customers and providers need to monitor complex contractual constraints of ML service that are strongly related to ML models and data. Therefore, establishing and monitoring comprehensive ML contracts are crucial in ML serving. This paper demonstrates a set of features and utilities of the QoA4ML framework for ML contracts.",

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AB - Using machine learning (ML) services, both service customers and providers need to monitor complex contractual constraints of ML service that are strongly related to ML models and data. Therefore, establishing and monitoring comprehensive ML contracts are crucial in ML serving. This paper demonstrates a set of features and utilities of the QoA4ML framework for ML contracts.

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