AI-Driven Predictive Maintenance Framework for Cloud-Native Financial Systems
Keywords:
Predictive Maintenance, Cloud-Native Systems, Financial Technology, Deep Learning, Lstm Networks, Attention Mechanisms, Anomaly Detection, MLOps, Microservices, ObservabilityAbstract
Financial technology systems operate in highly dynamic microservice-based environments that requirecontinuous availability and reliability to support critical transaction processing operations. Traditionalmonitoring and alerting mechanisms usually act post-factum, after the performance degradation has already occurred, which results in service disruptions
References
Jovani Dalzochio et al., "Machine learning and reasoning for predictive maintenance in Industry 4.0: Current status and challenges," Computers in Industry, Volume 123, 2020. Available: https://www.sciencedirect.com/science/article/abs/pii/S0166361520305327
Ravikumar Perumallaplli, "Predictive Maintenance In Cloud Infrastructure: A Machine Learning Framework," SSRN Electronic Journal, 2021. Available: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5228213
