Packet Capture & Deep Diagnostics
Sometimes SNMP counters and CLI outputs don’t tell the whole story. That’s where packet captures come in. Instead of relying on manual Wireshark sessions and ad-hoc commands, I design automation to trigger, collect, and analyze captures across devices on demand.
My Approach
On-Demand Capture Triggers – automate PCAPs via CLI or API hooks when certain conditions are met (e.g., high error rates, session drops).
Automated Parsing – scripts flag error signatures like retransmissions, malformed packets, or excessive latency without needing to open Wireshark.
Correlated Diagnostics – tie PCAP data into syslog, SNMP, and CLI results for a full context view.
Storage & Retrieval – captures archived with metadata (time, device, trigger condition) for compliance and later analysis.
Advancing Further
I continue to expand methodology toward:
Context-Aware Triggers – dynamic rules that launch captures only when anomalies are detected, saving time and resources.
AI-Assisted Parsing – NLP-driven summaries of packet captures that highlight anomalies in plain English.
Integrated RCA Workflows – PCAP analysis tied directly into troubleshooting playbooks and escalation paths.
Why It Matters
Packet captures are the ground truth of networking, but they’re traditionally slow and manual to work with. By automating the capture and parsing pipeline, I cut resolution time and bring deep visibility into everyday troubleshooting — without the bloat of legacy NMS tools.