Welcome to the fifth blog post in our series AI Network Monitoring: Bridging the NPM Gap with ChatGPT. Here are some real-world examples of how ChatGPT can bridge the gap in Network Performance Monitoring (NPM) by analyzing NPM tools’ findings and providing actionable solutions or next steps.
- Example 1: Packet Loss Analysis
- Analysis: An NPM tool reveals a consistent pattern of packet loss in a network segment during peak usage hours.
- ChatGPT’s Response: ChatGPT interprets the issue and explains that the observed packet loss is akin to cars getting stuck in a traffic jam on a highway. It suggests that the network might be congested during busy periods, leading to packet loss.
- Solution: ChatGPT recommends load balancing the traffic using a tool like HAProxy, distributing it evenly across multiple servers. It provides step-by-step instructions for configuring HAProxy to address the congestion issue.
- Example 2: DNS Resolution Latency
- Analysis: The NPM tool reports increased DNS resolution latency, causing delays in accessing web applications.
- ChatGPT’s Response: ChatGPT likens the DNS resolution process to a library’s card catalog system, where finding a book takes longer due to disorganized cards. It explains that inefficient DNS resolution can lead to latency.
- Solution: ChatGPT suggests implementing a local caching DNS server, like a dedicated librarian who organizes frequently requested books. It provides guidance on configuring a DNS caching server and recommends using tools like BIND or dnsmasq.
- Example 3: Security Alert from Intrusion Detection System (IDS)
- Analysis: An intrusion detection system (IDS) generates a security alert about a potential breach.
- ChatGPT’s Response: ChatGPT uses the metaphor of a vigilant sentry guarding a fortress to explain the IDS’s role. It states that the IDS detected a suspicious activity, much like the sentry spotting an intruder.
- Solution: ChatGPT advises the engineer to investigate the alert further. It provides a checklist for incident response, including isolating affected systems, collecting forensic data, and contacting the security team for a comprehensive analysis.
- Example 4: High CPU Utilization on Router
- Analysis: The NPM tool indicates high CPU utilization on a critical router.
- ChatGPT’s Response: ChatGPT likens the router’s CPU to the engine of a car running at high RPM, potentially causing overheating and breakdown.
- Solution: ChatGPT recommends optimizing router configurations, particularly reviewing access control lists (ACLs) and routing tables. It advises the engineer to identify and offload CPU-intensive tasks like encryption or packet inspection to dedicated hardware modules.
- Example 5: Bandwidth Saturation in Data Center
- Analysis: The NPM tool reveals that bandwidth in the data center is nearing saturation, leading to slow data transfers.
- ChatGPT’s Response: ChatGPT paints a picture of a crowded highway with too many vehicles and not enough lanes, illustrating the bandwidth saturation problem.
- Solution: ChatGPT suggests implementing link aggregation (LACP) to bundle multiple network links into a single high-capacity connection, expanding the “lanes” on the highway. It provides instructions for configuring LACP on network switches to alleviate bandwidth constraints.
- Example 6: Collaboration with Security Team
- Analysis: The NPM tool detects a sudden spike in unusual network traffic patterns.
- ChatGPT’s Response: ChatGPT emphasizes the importance of collaboration and likens it to a detective team working together to solve a mystery.
- Solution: ChatGPT advises the engineer to notify the security team immediately and shares a checklist for sharing relevant information, conducting joint investigations, and mitigating potential security threats collaboratively.
These examples demonstrate how ChatGPT can provide insights, explanations, and practical solutions in a creative and relatable manner. By combining technical expertise with metaphorical and analogical reasoning, ChatGPT empowers network engineers to understand, address, and prevent network issues effectively, in any way they want to think about it.
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:
- AI Network Monitoring: Bridging the NPM with ChatGPT: Introduction
- Expert Advice for Network Monitoring
- Interpretation and Insights for Complex Networks
- Recommendations for Network Issue Resolution
- Examples of ChatGPT in Action
- The Future of AI based Network Monitoring (coming soon)
- Integration into NPM Tools (coming soon)
- Next Steps for AI Network Monitoring (coming soon)
- How to Become an Expert Prompt Engineer for Network Engineering (coming soon)
- Conclusion (coming soon)
