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ISSN: 2634-8853 | Open Access

Journal of Engineering and Applied Sciences Technology

Intent-Based Networking in Multi-Cloud Environments
Author(s): Abhishek Singh
The rapid adoption of multi-cloud environments has introduced new complexities in network management, necessitating innovative solutions to ensure seamless operation, security, and performance. Intent-Based Networking (IBN) emerges as a transformative approach, leveraging automation, artificial intelligence, and machine learning to align network operations with high-level business intents. This paper delves into the integration of IBN within multi-cloud environments, examining its architectural design, benefits, and challenges.

The study begins by exploring the core components of IBN, including intent definition and translation, policy management, and network analytics. It then discusses the unique characteristics of multi-cloud architectures, emphasizing the need for interoperability and dynamic resource allocation. By integrating IBN with multi-cloud environments, organizations can achieve enhanced automation, improved security, and optimized performance.

However, the implementation of IBN in multi-cloud settings is not without challenges. Technical complexities, scalability issues, and organizational resistance are significant barriers that must be addressed. This paper proposes solutions such as advanced AI techniques and comprehensive training programs to overcome these obstacles.

Furthermore, the paper highlights future trends and innovations in IBN, including the impact of emerging technologies like 5G and edge computing. It also identifies potential research directions and collaboration opportunities between academia and industry.

In conclusion, Intent-Based Networking holds great promise for revolutionizing network management in multi-cloud environments. By aligning network operations with business intents, IBN can provide the flexibility, control, and efficiency required to navigate the complexities of modern IT landscapes. This paper aims to provide a comprehensive understanding of IBN's potential and pave the way for future advancements in this field.