From Incident to Evidence: Autonomous AIOps for DORA-Ready Financial DevOps Self-Healing Remediation with  Traceability and Audit-Grade Proof

Amol Diwakar Agade; Samta Balpande

doi:10.36948/ijfmr.2025.v07i06.72540

From Incident to Evidence: Autonomous AIOps for DORA-Ready Financial DevOps Self-Healing Remediation with Traceability and Audit-Grade Proof

Author(s)	Amol Diwakar Agade, Samta Balpande
Country	United States
Abstract	Regulated finance platforms face competing pressures. They must accelerate deployment velocity while demonstrating operational resilience. They must also prove that security controls are effective and that all changes are traceable and well-governed. These requirements exist under tight regulatory regimes such as the EU Digital Operational Resilience Act (DORA) [1]. Conventional AIOps helps speed up issue detection and diagnosis. However, full automation of remediation is held back by policy rules, audit requirements, and safety constraints. In this paper, we propose a compliance-bound autonomous AIOps architecture based on three key elements: multi-agent reasoning, policy-as-code gates, and GitOps-based execution. The combination of these elements allows self-healing behavior while generating audit-grade evidence. We introduce an evidence-first remediation loop that automatically generates verifiable artifacts. These artifacts include attestations, policy decisions, and post-action validations aligned with defined control objectives. We used two public operations datasets to measure improvements: incident process logs and telemetry benchmarks. We also created a reproducible evaluation harness. We measured improvements in detection, recovery, intervention load, and compliance proof latency. Across 240 simulated incident episodes derived from these public datasets, our approach achieved significant operational gains. Mean time to detect (MTTD) reduced by 43.5%. Mean time to restore (MTTR) reduced by 38.2%. Manual intervention rate dropped by 55.9%. The benefits for controls and audit operations were even more significant. Audit preparation effort reduced by 68.7%. The evidence package latency dropped by 74.1%. All improvements occurred while maintaining policy constraint compliance. We also discussed how these patterns can be applied to other regulated industries. Healthcare, critical infrastructure, and insurance all face similar challenges. In these sectors, automated remediation must remain compliant, reviewable, and explainable.
Keywords	AIOps, autonomous remediation, self-healing infrastructure, DevOps, SRE, DORA, policy-as-code, audit evidence, GitOps, OpenShift.
Field	Engineering
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-11-08
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.72540

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From Incident to Evidence: Autonomous AIOps for DORA-Ready Financial DevOps Self-Healing Remediation with Traceability and Audit-Grade Proof

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