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The increasing reliance on microservices architecture (MSA) in financial systems has led to improved scalability, modularity, and fault tolerance. However, due to the distributed nature of microservices, cascading failures pose a significant risk to financial applications, leading to service disruptions and financial losses. This research presents a resilient microservices architecture that integrates AI-driven observability tools to predict and mitigate cascading failures in financial platforms such as Guidewire Cloud. The study explores key principles of microservices design, AI-based observability mechanisms, fault mitigation strategies, and compliance requirements. By embedding AI-powered monitoring, anomaly detection, and automated incident response, financial institutions can achieve enhanced system resilience, ensuring high availability, security, and regulatory compliance.
Mahender Singh (Sat,) studied this question.