Managing Digital Infrastructure Through AI-Driven Microservices that Adapt Based on Continuous Machine Learning Model Feedback
Keywords:
AI-driven microservices, machine learning feedback, adaptive infrastructure, cloud orchestration, digital infrastructure, DevOps, MLOps, real-time analyticsAbstract
This paper explores the integration of artificial intelligence with microservices architecture for the adaptive management of digital infrastructure. Through continuous feedback from machine learning models, infrastructure components can dynamically self-optimize, respond to load variations, and enhance operational resilience. This AI-driven methodology transforms traditional static infrastructure into intelligent systems capable of learning and evolving over time. By examining current trends, systems architecture, and adaptation strategies, the paper demonstrates how organizations can harness machine learning feedback to automate and scale infrastructure efficiently.
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Copyright (c) 2020 Liane Marcia Moriarty (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
