Intelligent Deployment Orchestration Using ML for Multi-Environment CI/CD Pipelines
Author(s): Hariprasad Sivaraman
Publication #: 2411104
Date of Publication: 05.07.2020
Country: USA
Pages: 1-7
Published In: Volume 6 Issue 4 July-2020
DOI: https://doi.org/10.5281/zenodo.14250622
Abstract
Continuous Integration (CI)/Continuous Development (CD) pipelines play an important role in stabilizing the release cycle of modern software development world. Though, deployments to multiple environments (dev, stg, prod) have their own set of problem statements. This work discusses a ML based deployment orchestration model to optimize multi-array CI/CD pipelines. Using predictive modeling and real-time decision-making, this orchestration system adaptively responds to different deployment conditions to achieve optimal resource utilization, risk-management, and minimized downtime. This paper presents the architecture of the proposed model and its components with a use-case example of how it can improve deployment efficiency and reliability.
Keywords: CI/CD Pipelines, Deployment Orchestration, Machine Learning, Multi-Environment, Automation, Resource Optimization
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