International Scientific Journal of Engineering and Management

An International Scholarly || Multidisciplinary || Open Access || Indexing in all major Database & Metadata
The journal follows the UGC Guidelines and is evaluated for inclusion in the Web of Science
ISSN: 2583-6129

Impact Factor: 8.072

Optimizing Cloud-Native Software Development Life Cycles (SDLC) through Policy-as-Code (PaC) and Intelligent Compliance Automation

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Optimizing Cloud-Native Software Development Life Cycles (SDLC) through Policy-as-Code (PaC) and Intelligent Compliance Automation

 

 

Pankaj Gupta

Pankaj.tp@gmail.com

 

 

Abstract
The software development lifecycle (SDLC) is now experiencing levels of speed and agility it never before experienced, due to microservices, containers, and serverless computing, all of which are part of today's ubiquitous cloud native architecture. As such, while we have seen unparalleled levels of agility as a result of these new architectural paradigms, they have also left behind many existing governance structures. As such, there exists a "compliance-velocity" paradox, where manual review by regulators is now the biggest barrier to deploying applications to production. The purpose of this research was to develop an advanced Intelligent Compliance Automation framework that would provide much greater flexibility than the traditional gatekeeping models of compliance. A key component of this model is the Policy-as-Code (PaC) paradigm, which represents formally defined security and operational guardrails as executable code that can be versioned like application code. Our Intelligent Policy Engine (IPE), which is a novel integration of Declarative Logic (Open Policy Agent/Rego) and Machine Learning (ML) technologies, will enable predictive drift detection and autonomous remediation, unlike other reactive auto-scaling and monitoring systems. Additionally, our IPE provides a "Shift-Smart" methodological framework to utilize natural language processing (NLP) to close the semantic gap between complex regulatory text and machine readable policy enforcement. Testing of our proposed system across multiple large scale cloud-based testbeds, showed a 65% reduction in compliance-related delay in deployment, and an increase in audit fidelity of 98.5%. These results indicate that intelligent and automated governance is not just a luxury of operationally oriented organizations, but a strategic necessity to maintain a compliant and resilient position within the rapidly changing 2025 cloud native environment.

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