https://iphopen.org/index.php/se/issue/feed 2025-11-11T06:10:20+00:00 Aasik Hussain khanaasik95@gmail.com Open Journal Systems <p><strong>IPHO-Journal of Advance Research in Science And Engineering.<a href="https://portal.issn.org/resource/ISSN/3050-8797"><em>(e-ISSN.3050-8797, p-ISSN 3050-9270) </em></a></strong>Computer Science is the systematic study of the feasibility, structure, expression. It is one of the fastest growing career fields in modern history.Mechanical engineering is a discipline of engineering that applies the principles of engineering, physics and materials science for analysis, design,Electrical and electronics engineering is engineering branch, which focuses on the use of electricity on different forms. It is the branch which deals with the uses of biomechanics, aerodynamics, fluid mechanics, automobiles, hydraulics, infrastructure, designing, analysis of geotechnical studies</p> https://iphopen.org/index.php/se/article/view/368 2025-11-11T06:01:30+00:00 SREEJITH KAIMAL no_reply@gmail.com

<p>Migration to the cloud has moved from infrastructure renewal to strategic programs demanding holistic frameworks for dealing with vendor dependencies, regulatory challenges, and geopolitical risks. This framework proposes systemic methods that integrate workload categorization, vendor-independent architectures, data governance policies, and geopolitical risk management. Workload categorization creates criticality hierarchies and determines system interdependencies and technological constraints. Mitigation of vendor lock-in uses open standards, containerization, and Infrastructure-as-Code that is cross-platform agnostic. Data portability plans utilize AI-powered interoperability supporting smooth multi-cloud operations.Geopolitical risk policies integrate AI-based monitoring and area failover settings, overcoming regulation differences and service outages.Financial assessment indicates active-active deployments calling for double to triple the cost of active-passive arrangements, with cold backup options demanding low recurring expenses. The model offers systematic methods for dealing with sophisticated regulatory environments while preserving operational efficiency and strategic flexibility in modern multi-cloud platforms.</p>

2025-11-11T00:00:00+00:00 Copyright (c) 2025 IPHO-Journal of Advance Research in Science And Engineering https://iphopen.org/index.php/se/article/view/369 2025-11-11T06:10:20+00:00 HARDIK R PATEL no_reply@gmail.com

<p>Standard credit risk modeling infrastructures face serious limitations in serving modern needs for near real-time decisioning, regulatory flexibility, and computational scale. This case details the transformation of a multinational financial institution'scredit risk analytics infrastructure by introducing Kubernetes-based distributed infrastructure. The containerized architecture deploys GPU-accelerated compute nodes, service meshes for secure communications, and observability frameworks for monitoring thereliability of the system.Results from the implementation demonstrated remarkable reductions in Monte Carlo simulation run times,machine learning model training times, and regulatory reporting cycles, while increasing overall system uptime and deployment speed. In addition to the technical performance improvements, the transformation created compliance-by-design in the system through embedded governance controls and alignment across organizational roles of data scientists, engineers, and compliance officers. Ongoing challenges faced in the transformation include the cost to operate in the cloud, governance of data in a jurisdiction, and accommodating the workforce for acceptance of the containerized environment. Overall, the case demonstrates that cloud-native architectures could serve as a strategic enabler to operational resilience and regulatory competitiveness, with many insights into the modernizing infrastructure that financial institutions are faced with from a perspective of compliance.</p>

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