AI-Powered SIP Troubleshooting: Analyzing SIP Calling with ChatGPT

By John Meersma | 57 Min Video

Join us for a deep dive into AI-powered troubleshooting with ChatGPT, where you’ll learn to analyze and interpret SIP debug messages and call traces to enhance troubleshooting efficiency. We highlight the essentials of Webex Calling and discuss key features to help optimize your collaboration environment.

 
 
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Understanding SIP Traces and Debug Logs

  • The session reviews SIP request/response flow, identifying key call setup, teardown, and SDP messaging patterns.
  • Demonstrates capturing traces using Wireshark, CUCM RTMT, and TranslatorX to derive detailed call path data.

ChatGPT–Enhanced Analysis

  • Highlights how to prompt ChatGPT effectively with SIP trace snippets to decode complex protocol operations.
  • Showcases ChatGPT’s ability to automatically flag errors (e.g., 403 Forbidden, missing SDP) and propose corrective actions.
  • Emphasizes maintaining structured context (timestamps, call IDs) in prompts for accurate AI-assisted analysis.

Troubleshooting Common SIP Issues

  • Identifies frequently seen problems: one-way audio, registration failures, SIP header mismatches, and codec negotiation conflicts.
  • Demonstrates how AI can pinpoint root causes and suggest actionable fixes more efficiently than manual parsing.

SIP Troubleshooting Tools

Walks through tools like:

  • Wireshark: filtering and interpreting SIP packets
  • CUCM RTMT: real-time call trace monitoring
  • TranslatorX: translating debug logs into readable formats
  • CUBE DNA and Collaboration Analyzer: enriched SIP analysis.

Workflow Integration and Best Practices

  • Encourages combining AI with traditional tools in a hybrid troubleshooting workflow—capture logs, query ChatGPT, verify insights, and implement fixes.
  • Highlights benefits of structured prompting, including specifying line context, entire call IDs, and relevant metadata for AI accuracy.

Efficiency Gains and Professional Impact

  • AI assistance reduces time-to-resolution, cuts down on manual trace interpretation, and lowers the learning curve for junior engineers.
  • Empowers teams to scale troubleshooting capabilities, share AI-enabled debug patterns, and build repeatable analysis templates.

Final Takeaway

  • Capture SIP debug logs via Wireshark, RTMT, and TranslatorX.
  • Use structured prompts to feed traces into ChatGPT.
  • Let AI interpret errors and suggest preventive or corrective steps.
  • Validate results and apply fixes via CUCM, CUBE, or PSTN settings.
  • Wrap the solution into a hybrid workflow that streamlines SIP troubleshooting across teams.

 

Instructor Bio:

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John Meersma has nearly twenty years of experience working in the IT industry. His areas of focus are Collaboration; voice, video, and SIP, in addition to routing and switching. John has put his enthusiasm for data networking and his love of working with people to work as an instructor. Over the past two decades, he has taught various IT courses to diverse audiences.

John’s past employment includes monitoring the global WAN for a large pharmaceutical company, spending over five years as a university professor of Cisco and Microsoft curriculum, training engineers for Fortune 50 companies, and independent consultation for small and mid-sized organizations. John has also created and delivered custom courses for Dell Computers. He was also co-owner of an IT consulting firm serving non-profit organizations throughout southwest Michigan. He designed and implemented secure data storage solutions for local hospitals and installed Voice over IP infrastructure for area school districts. 

 
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