Soha Rawas, Agariadne Dwinggo Samala, Aprilla Fortuna
As cloud computing evolves, traditional resilience strategies must adapt to new challenges. This paper introduces CRISP, Cloud Resilient Infrastructure for Self-Healing Platforms, a pioneering framework designed to enhance cloud resilience through autonomous fault management. By leveraging advanced machine learning, predictive analytics, and dynamic adaptation, CRISP Clouds provides a robust solution for real-time fault detection, diagnosis, and automated recovery. Our findings highlight CRISP Clouds’ ability to significantly improve system agility, minimize downtime, and optimize resource usage. This work presents a critical advancement in resilience engineering, setting the stage for future innovations in cloud technology. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.
Faculty of Science, Department of Mathematics and Computer science, Beirut Arab University, Soha, Beirut, Lebanon; Faculty of Engineering, Universitas Negeri Padang, West Sumatera, Indonesia
