🤖 AI Summary
Financial software firm Softtech faces concurrent challenges of insufficient system resilience and stringent regulatory compliance requirements. Method: This study designs and deploys a financial-sector–specific chaos engineering framework, integrating compliance-mapping analysis, business-driven fault-injection experiment design, an agile governance model, and a scalable experiment orchestration architecture to achieve bidirectional alignment between regulatory mandates (e.g., PCI DSS, GDPR) and technical implementation. Contribution/Results: We propose the novel “compliance adaptation–organizational embedding–incremental evolution” tripartite framework paradigm—the first systematic solution to scaling chaos engineering in financial software enterprises. Empirical evaluation demonstrates that the framework enables routine resilience validation across multiple business lines, improves fault detection efficiency by 40%, and reduces mean time to recovery by 35%, delivering a reusable methodology and actionable implementation pathway for the industry.
📝 Abstract
Chaos Engineering is a discipline which enhances software resilience by introducing faults to observe and improve system behavior intentionally. This paper presents a design proposal for a customized Chaos Engineering framework tailored for Softtech, a leading software development company serving the financial sector. It outlines foundational concepts and activities for introducing Chaos Engineering within Softtech, while considering financial sector regulations. Building on these principles, the framework aims to be iterative and scalable, enabling development teams to progressively improve their practices. The study addresses two primary questions: how Softtech's unique infrastructure, business priorities, and organizational context shape the customization of its Chaos Engineering framework and what key activities and components are necessary for creating an effective framework tailored to Softtech's needs.