International Journal of Computer Techniques Volume 12 Issue 5 | AI-Driven Intelligent Microservices Orchestration and Auto- Healing in Multi-Cloud Environments
International Journal of Computer Techniques Volume 12 Issue 5 | AI-Driven Intelligent Microservices Orchestration and Auto- Healing in Multi-Cloud Environments
This paper analyzes AI-driven orchestration and auto-healing mechanisms for microservices in multi-cloud environments. It explores how machine learning, reinforcement learning, and LLMs can reduce downtime, optimize resource usage, and improve fault tolerance. The proposed framework achieves up to 87% reduction in service downtime and 65% improvement in resource efficiency, outperforming traditional orchestration methods.
AI-powered orchestration offers transformative benefits for managing distributed microservices across multi-cloud platforms. The study highlights significant gains in reliability, cost-efficiency, and scalability. Future directions include integrating explainable AI, federated learning, and carbon-aware scheduling for sustainable cloud-native systems.
References
Includes 44+ references from IEEE, ACM, Springer, and O’Reilly covering microservices architecture, cloud orchestration, AI-based fault recovery, and multi-cloud optimization strategies.
