Generative AI for Cloud Automation: Revolutionizing Infrastructure Optimization and Threat Detection
DOI:
https://doi.org/10.63282/3050-9262.IJAIDSML-V4I2P109Keywords:
Generative AI, Cloud Automation, Infrastructure Optimization, Threat Detection, AI-Driven Cybersecurity, Dynamic Resource Allocation, Predictive Maintenance, Performance OptimizationAbstract
The rapid growth of cloud computing has led to increasingly complex infrastructures, necessitating innovative solutions for optimizing resources and securing systems. Generative Artificial Intelligence (AI), a subset of AI that focuses on creating new data, holds significant potential for enhancing cloud automation. This paper explores the application of generative AI in two critical areas of cloud computing: infrastructure optimization and threat detection. In terms of optimization, generative AI models enable dynamic resource allocation, predictive maintenance, and performance optimization, leading to cost savings, energy efficiency, and improved system reliability. Regarding cybersecurity, generative AI is used to enhance intrusion detection systems (IDS), automate incident response, and improve threat intelligence. While the integration of generative AI presents challenges, including data privacy concerns and ethical implications, its transformative role in cloud environments is undeniable. This paper also highlights the future potential of generative AI in further advancing cloud infrastructure management and cybersecurity practices
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