The Transformative Impact of AI Ops/ML and Observability in Automating Networking Operations and Network Security

Authors: Mohit Bajpai

DOI: https://doi.org/10.5281/zenodo.14208771

Short DOI: https://doi.org/g8rrdm

Country: USA

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Abstract: The rapid advancements in Artificial Intelligence and Machine Learning have revolutionized various domains, including the field of network operations and security. This technical article explores the advantages of leveraging AI Ops/ML in automating and optimizing networking operations and network security. The paper discusses the key challenges faced in modern network environments, such as the increasing complexity, dynamic traffic patterns, and evolving security threats. It then delves into the role of AI/ML in addressing these challenges, highlighting its ability to enable autonomous and intelligent network operations, enhance security measures, and streamline network management. [1] [2] The article also presents a detailed deployment architecture, showcasing the integration of AI/ML components within the network ecosystem.

Keywords: AI Ops, Machine Learning, Network Operations, Network Security, Automation, Intelligent Networks, Observability, Prometheus, Splunk.

Paper Id: 231633

Published On: 2023-07-05

Published In: Volume 11, Issue 4, July-August 2023

Cite This: The Transformative Impact of AI Ops/ML and Observability in Automating Networking Operations and Network Security - Mohit Bajpai - IJIRMPS Volume 11, Issue 4, July-August 2023. DOI 10.5281/zenodo.14208771

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