Amol Diwakar Agade

AI-Powered Chaos Engineering for Resilient Banking: Real-Time Fault and Threat Detection

Abstract:

Modern banking platforms must deliver uninterrupted service despite rising architectural complexity, strict regulatory expectations, growing cyber risk, and constant pressure for faster change. Traditional resilience practices often rely on static controls, post-incident reviews, and manual analysis, which are too slow for distributed payment and core banking systems operating in real time.

This keynote presents a practical framework for resilience engineering in banking platforms using chaos engineering and AI feedback loops. The central idea is to make controlled fault injection more actionable by pairing it with machine learning models that continuously learn from telemetry, dependency behavior, deployment patterns, latency signals, and security events. Rather than treating chaos experiments as isolated tests, this approach uses them as part of an intelligent feedback system for improving operational resilience.

The session will examine how chaos experiments can simulate service degradation, dependency failures, tail-latency amplification, and control-plane disruptions across banking workloads. AI-driven analysis can then correlate these signals to identify weak points, detect abnormal behavior earlier, estimate blast radius, and prioritize remediation. By integrating observability, security telemetry, and intelligent decisioning, engineering teams can move from reactive incident response toward proactive resilience improvement.

Attendees will gain a practical blueprint for combining chaos engineering with applied intelligence to improve fault tolerance, reduce mean time to detect, strengthen security posture, and build more adaptive and trustworthy banking systems.

Profile:

Amol Diwakar Agade is a VP-level Platform & DevOps Enablement leader at Comerica Bank in Detroit, Michigan, with more than a decade of experience building and scaling CI/CD, reliability engineering, release governance, and operational resilience capabilities in regulated enterprise environments. His work focuses on banking platform modernization, intelligent automation, observability, and AI-driven software delivery.

He specializes in designing resilient delivery ecosystems that combine DevOps, site reliability engineering, policy-as-code, telemetry engineering, and predictive analytics to improve production stability without slowing delivery. His professional interests include anomaly detection, intelligent release controls, failure prediction, adaptive feedback loops, AIOps, and resilience engineering for complex distributed systems.

As a speaker, Amol brings a practitioner perspective on how applied intelligence can move beyond research concepts and become an operational capability in real-world banking environments. His work connects resilience, security, observability, software delivery, and governance to improve reliability and delivery confidence.