Leveraging Reinforcement Learning for Autonomous Cloud Management and Self-Healing Systems
Keywords:
Autonomous Cloud Management, Artificial Intelligence, Self-Healing, Self-Optimization, Cloud ComputingAbstract
This work investigates and enhances innovative methods for autonomous cloud management with artificial intelligence, specifically self-healing and self-optimization. The study uses AI based anomaly detection, predictive maintenance and automated recovery to derive self-healing. To self-optimize, it employs machine learning algorithms to analyze existing workload patterns, anticipate resource utilization demand, and adjust resources dynamically. These techniques are tested and validated in a simulated cloud environment in terms of performance metrics like response time, throughput, and resource utilization.
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