AI and Machine Learning Driving Network and Security Operations
Gartner coined the term AIOps in 2016 at a time when IT operations teams were starting to apply AI and machine learning techniques to streamline workflows for performance monitoring and event correlation. Since that time, the industry has made great strides in these areas, but NOC and SOC teams still rely on human decision-making and manual workflows for too many functions that could be highly automated.
Recently, Generative AI platforms based on Large Language Models (LLMs) have burst onto the scene and demonstrated astounding capabilities across diverse fields of art, science and commerce. GenAI is poised to have a major impact on IT Operations, helping to close the AIOps gap and drive automation deeper into network and security operations. GenAI can augment the abilities of operations personnel by simplifying complex workflows and performing tasks such as code generation so that operators don’t need to become expert programmers in order to leverage the power of network automation.
The ONUG Collaborative AI-Driven NOC/SOC Automation project team is evaluating a set of high-value use cases for AI-driven automation, which will be documented in a maturity model framework that ranges from near-term, low-risk/high-return opportunities to aspirational, art-of-the-possible, long-term goals. The primary objective is to educate enterprise IT operations teams so they are equipped to evaluate the use case requirements, technical challenges, infrastructure implications and security risks for utilizing AI and machine learning to automate a wide range of networking and security operations functions.
