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Written by Chris Bloom, LiveAction Senior Product Sales Specialist

Welcome to the second blog post in our series AI Network Monitoring: Bridging the NPM Gap with ChatGPT. In today’s post, we’ll delve into how ChatGPT can become your trusted companion, offering expert guidance for network monitoring.

ChatGPT can engage in natural language conversations, enabling network administrators to interact with it as they would with a human expert. This allows for clear communication of network issues and provides immediate responses.

The value of human-like conversations facilitated by AI, particularly ChatGPT, cannot be overstated in the context of Network Performance Monitoring (NPM). These AI-driven conversations offer a wide range of benefits that can enhance the efficiency and effectiveness of troubleshooting network issues.

Here is a deeper exploration of their advantages:

  • Constant Availability: AI is always accessible, 24/7. Unlike human experts who need rest and might not always be available when a network crisis strikes, AI-powered conversations are consistently accessible to assist network engineers whenever needed. This uninterrupted availability ensures that network issues can be addressed promptly, reducing downtime, and minimizing business disruptions. With remote work, and so many different skill sets spread though out different departments and time zones, it is great to have ChatGPT always ready and willing to answer any questions.
  • Unlimited Patience and Objectivity: AI never tires, gets annoyed, or forms judgments. It approaches every inquiry with the same level of patience and objectivity, regardless of the complexity or repetition of questions. This consistency is vital in the often-high-pressure world of network troubleshooting, where emotions can sometimes cloud judgment.
  • Endless Exploration: AI network monitoring can delve into any investigative path without hesitation. Unlike human experts who may be constrained by their knowledge and experience, AI can explore a multitude of possibilities and angles to uncover the root cause of network problems. It leaves no stone unturned, ensuring a comprehensive analysis. Ok, it may leave a few stones unturned, because of the limited data it can be preloaded with as part of the prompt, but no fear, just break the data into smaller chunks, and keep asking questions about it.
  • Continuous Learning: ChatGPT has the capacity to learn and adapt. As more data is provided and as network engineers become better at asking questions, AI continuously improves its responses and recommendations. It can adapt to evolving network configurations and challenges, providing increasingly precise insights over time. Again, preloading is the key here. Learning to input the analysis properly and in a compressed format will give ChatGPT the knowledge it needs to provide more informed answers to questions about problems
  • Idea Generation: ChatGPT doesn’t just provide solutions; it can also spark new ideas and approaches. Through conversational exchanges, ChatGPT can suggest innovative ways to address network issues, offering fresh perspectives that human experts might not have considered. This creative input can lead to more effective problem-solving and make the process more interesting. This is where metaphors and analogies can be used to explain problems to ChatGPT using terms from paradigms we may be more familiar with and allows ChatGPT to respond in those terms as well.
  • Rapid Scaling: For organizations with large and complex networks, AI-driven conversations can scale effortlessly. Whether you’re managing a small office network or a global infrastructure, using AI for network monitoring can adapt to the scope and complexity of the task without requiring additional personnel.
  • Reduced Dependency: While human expertise is invaluable, the ability of AI to handle routine or straightforward issues allows network engineers to focus on more complex challenges that require their specialized skills. AI complements human expertise, freeing up professionals to work on strategic initiatives.
  • Documentation and Knowledge Sharing: AI-driven conversations can document troubleshooting processes comprehensively. This documentation can be invaluable for training, knowledge sharing, and future reference, ensuring that best practices are consistently applied throughout the organization.
  • Improved Collaboration: AI can facilitate collaboration among network engineers by providing a common platform for discussing and addressing network issues. Engineers can share insights, seek assistance, and collectively arrive at solutions, streamlining teamwork and knowledge sharing.
  • Cost-Effective: AI-driven conversations offer cost-effective solutions, as they do not require the same level of compensation and benefits as human experts. This cost efficiency can be particularly appealing for organizations seeking to optimize their IT budgets. This is also why people will be losing their jobs, because other people will be able to use ChatGPT to do a whole lot more.

In summary, like every other domain area that AI has affected, ChatGPT-driven conversations in NPM are a massive game-changer and transforming how network engineering is done, and the speed at which it can be done. The constant availability, objectivity, adaptability, and capacity for idea generation makes ChatGPT an invaluable ally for network engineers. As AI technology continues to advance, the synergy between human expertise and ChatGPT-driven assistance will further enhance the efficiency and effectiveness of network troubleshooting, ultimately leading to more reliable and resilient network infrastructures.

Be on the look out for this 10 part blog series

Explaining how AI can bridge that gap and can help network engineers cover better manage their networks with the help of AI:

  1. AI Network Monitoring: Bridging the NPM with ChatGPT: Introduction
  2. Expert Advice for Network Monitoring
  3. Interpretation and Insights for Complex Networks
  4. Recommendations for Network Issue Resolution
  5. Examples of Maximizing Your NPM with ChatGPT
  6. The Future of AI based Network Monitoring (coming soon)
  7. Integration into NPM Tools (coming soon)
  8. Next Steps for AI Network Monitoring (coming soon)
  9. How to Become an Expert Prompt Engineer for Network Engineering (coming soon)
  10. Conclusion (coming soon)