AI-Enhanced Self-Healing Cloud Architectures for Data Integrity, Privacy, and Sustainable Learning

Abstract

In the era of digital transformation, the integrity and privacy of data have become paramount concerns for organizations and educational institutions alike. This chapter explores the concept of AI-enhanced self-healing cloud architectures, which leverage advanced artificial intelligence algorithms to automatically detect, diagnose, and rectify anomalies in real-time. By incorporating self-healing mechanisms, these architectures ensure data integrity and privacy while maintaining operational efficiency. The chapter discusses the underlying principles of these architectures, the role of machine learning in predictive maintenance, and the implications for sustainable learning environments. Case studies illustrate successful implementations and highlight the benefits of adopting such innovative solutions in cloud computing. Ultimately, this chapter advocates for a paradigm shift towards more resilient cloud infrastructures that not only enhance data security but also support sustainable practices in educational contexts.