Machine Learning-Enhanced Release Management for Large-Scale Content Platforms: Automating Deployment Cycles and Reducing Rollback Risks
Keywords:
machine learning, artificial intelligenceAbstract
ML and AI may improve release management systems for key entertainment content platforms, according to this research. Complex software updates cause operational pauses, rollbacks, and deployment errors, especially on high-demand content platforms. Traditional release management systems' manual monitoring is wasteful, error-prone, and tedious. Platform expansion demands robust, automated, and reliable systems.
Machine learning models may be used in code integration, build validation, testing, and deployment, studies show. Predicting deployment mistakes, improving deployment windows, and evaluating rollback risk in real time are important difficulties in software distribution for high-demand content platforms. ML algorithms may help. Automating deployment cuts release failures and time to market.
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