Real-Time Risk Compliance in DevOps through AI-Augmented Governance Frameworks
Keywords:
Real-Time Risk Compliance, AI-Augmented Governance, DevOps, Continuous Monitoring, Predictive Analytics, Risk Management, Automation in DevOps, Compliance Automation, Machine Learning, Regulatory Adherence, Risk Detection, Security and Compliance, Cloud-Based Platforms.Abstract
In a constantly growing DevOps environment, there is a need to monitor the risks needing compliance in real time to meet security and regulation needs. This paper focuses on applying AI systems in governance structures where machine learning (ML) and predictive analytics enhance risk detection and mitigation. Compliance checks lower human interaction in identifying deviations and operational risks. An example of AI in action for DevOps pipeline risk detection is shown through a simulation; a case study from the financial industry shows its relevance. This paper discusses issues like integration, security, and possibly increasing the capacity of the AI system and possible solutions like deploying compact AI systems, anonymizing data, and cloud computing. Here, AI requires secure, efficient, and self-healing DevOps systems.
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