Machine Learning Approaches for Resource Consumption Assessment

Kirran Priya Nookala

doi:10.70528/IJLRP.v7.i5.2279

Machine Learning Approaches for Resource Consumption Assessment

Author(s)	Kirran Priya Nookala
Country	India
Abstract	Sonatype Nexus is a widely adopted repository management platform used in DevOps and Continuous Integration/Continuous Delivery (CI/CD) environments for the efficient storage, management, and retrieval of binary artifacts. It serves as a centralized repository for software packages, dependencies, container images, and build artifacts, enabling development teams to collaborate effectively while maintaining the integrity and security of the software supply chain. As software development activities increase, a large volume of artifacts is continuously uploaded to multiple repositories within each Nexus instance, resulting in rapid growth in storage utilization. Managing repository storage is a critical responsibility of Nexus administrators. When repository storage exceeds the available disk capacity, the Nexus server may become unavailable, disrupting software development, build, and deployment activities across the organization. Although Nexus provides automated cleanup tasks for removing obsolete artifacts, these mechanisms have limitations because frequently accessed artifacts cannot be deleted without affecting development workflows. Consequently, administrators lack an effective mechanism to predict future storage consumption and proactively prevent storage-related failures.This paper addresses this challenge by proposing a machine learning–based approach using Univariate Linear Regression Analysis to forecast repository storage utilization. Historical repository usage data are analyzed to derive a regression equation that models the relationship between time and storage consumption. The resulting predictive model estimates future repository growth, enabling administrators to anticipate storage requirements, schedule infrastructure expansion, and prevent unexpected service interruptions. The proposed approach enhances repository availability, reduces administrative overhead, minimizes downtime, and supports proactive capacity planning for enterprise-scale DevOps environments.
Keywords	Sonatype Nexus Repository Manager, NXRM, Release Repository, Snapshot Repository, Docker registry, npm repository, Maven, Nuget, LDAP, Linear Regression Analysis.
Published In	Volume 7, Issue 5, May 2026
Published On	2026-05-08
DOI	https://doi.org/10.70528/IJLRP.v7.i5.2279

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Machine Learning Approaches for Resource Consumption Assessment

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