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Automating Staged Rollout with Reinforcement Learning

2022-04-01 21:22:39
Shadow Pritchard, Vidhyashree Nagaraju, Lance Fiondella
arXiv_AI
   
Abstract

Staged rollout is a strategy of incrementally releasing software updates to portions of the user population in order to accelerate defect discovery without incurring catastrophic outcomes such as system wide outages. Some past studies have examined how to quantify and automate staged rollout, but stop short of simultaneously considering multiple product or process metrics explicitly. This paper demonstrates the potential to automate staged rollout with multi-objective reinforcement learning in order to dynamically balance stakeholder needs such as time to deliver new features and downtime incurred by failures due to latent defects.

Abstract (translated)

URL

https://arxiv.org/abs/2204.02189

PDF

https://arxiv.org/pdf/2204.02189.pdf

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