Amol 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 simple: controlled fault injection becomes far more valuable when paired with machine learning models that continuously learn from telemetry, dependency behavior, deployment patterns, latency signals, and security events. Instead of treating chaos experiments as isolated tests, this approach turns them into an intelligent feedback system for production resilience.

The session will show how chaos experiments can be used to simulate service degradation, dependency failure, tail-latency amplification, and control-plane disruptions across banking workloads. AI-driven analysis then correlates those signals to identify weak points, predict abnormal behavior earlier, estimate blast radius, and prioritize remediation actions. By integrating observability, security telemetry, and intelligent decisioning, teams can move from reactive firefighting to proactive resilience improvement.

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

Profile:

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

Amol specializes in designing resilient delivery ecosystems that combine DevOps, SRE, policy-as-code, telemetry engineering, and predictive analytics to improve stability without slowing innovation. He is particularly interested in applying AI and ML to operational decision-making, including anomaly detection, intelligent release controls, failure prediction, and adaptive feedback loops for complex distributed systems.

As a speaker, Amol brings a practitioner’s perspective on how applied intelligence can move beyond theory and become an operational capability in real-world banking environments. His sessions help engineering leaders connect resilience, security, observability, and governance into actionable systems that improve both reliability and delivery confidence.