Platform Engineering for Intelligent Cloud-Native Enterprises with AI and ML Pipelines along with Continuous Integration Security and Performance Analytics

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Published: 2024-07-05
DOI: https://doi.org/10.15662/IJRPETM.2024.0704004
Keywords:
Cloud-Native Architecture, Platform Engineering, Artificial Intelligence (AI), Machine Learning (ML) Pipelines, Continuous Integration (CI/CD), Security and Compliance, Performance Analytics

Main Article Content

David Mattias Blomqvist
Machine Learning Engineer, Sweden

Abstract

The rapid evolution of enterprise applications necessitates robust and intelligent cloud-native platforms that can seamlessly integrate artificial intelligence (AI) and machine learning (ML) pipelines while ensuring continuous integration, security, and performance optimization. Traditional monolithic architectures often fail to meet the scalability, agility, and reliability requirements of modern enterprises. This paper presents a comprehensive framework for platform engineering in cloud-native enterprises, emphasizing modular architecture, containerization, microservices orchestration, and automated CI/CD pipelines. The framework integrates secure AI/ML pipelines, performance monitoring, and predictive analytics to support real-time decision-making across business domains. Emphasis is placed on security mechanisms, including identity and access management, encryption, and compliance adherence, ensuring data integrity and privacy. We also discuss methods for performance analytics, enabling enterprises to detect bottlenecks, optimize resource utilization, and maintain service-level objectives. Case scenarios in healthcare, finance, and insurance illustrate the applicability of the framework. The findings demonstrate that intelligent platform engineering not only enhances operational efficiency but also accelerates innovation by facilitating rapid deployment, continuous learning, and system observability. This study contributes a unified approach to designing secure, scalable, and performance-optimized cloud-native enterprise platforms empowered by AI and ML capabilities.

Article Details

Issue

Vol. 7 No. 4 (2024): International Journal of Research Publications in Engineering, Technology and Management

Section

Articles

How to Cite

Platform Engineering for Intelligent Cloud-Native Enterprises with AI and ML Pipelines along with Continuous Integration Security and Performance Analytics. (2024). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 7(4), 10844-10850. https://doi.org/10.15662/IJRPETM.2024.0704004

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