Intent-driven scheduling of backup jobs
Souvik Dutta, Suri Brahmaroutu

TL;DR
This paper introduces a framework for scheduling backup jobs that respects existing schedules and intent-based constraints, optimizing for specific goals without disruption, validated on real-world data.
Contribution
It proposes a novel intent-driven scheduling framework specifically designed for backup jobs, accommodating various constraints and ensuring minimal disruption.
Findings
Effective scheduling respecting existing jobs and constraints
Validated on real-world backup data
Improves adherence to scheduling intents
Abstract
Job scheduling under various constraints to achieve global optimization is a well-studied problem. However, in scenarios that involve time-dependent constraints, such as scheduling backup jobs, achieving global optimization may not always be desirable. This paper presents a framework for scheduling new backup jobs in the presence of existing job schedules, focusing on satisfying intent-based constraints without disrupting current schedules. The proposed method accommodates various scheduling intents and constraints, and its effectiveness is validated through extensive testing against a variety of backup scenarios on real-world data from Veritas Netbackup customer policies.
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Taxonomy
TopicsScheduling and Optimization Algorithms · Distributed and Parallel Computing Systems
