🤖 AI DevOps Debugger — Turning Production Logs into Actionable Insights with Copilot CLI

This is a submission for the GitHub Copilot CLI Challenge

What I Built

As a backend engineer, I’ve spent a lot of time debugging production issues — memory leaks, Redis disconnections, unhandled promise rejections, timeout errors, and mysterious crashes that only appear in production.

Logs usually tell us what happened, but not why.

So I built AI DevOps Debugger, a terminal-based CLI tool that transforms raw production logs into structured, actionable insights using GitHub Copilot CLI.

🔍 What It Does

📂 Analyzes Node.js application logs

🧠 Detects common production failure patterns

📊 Categorizes issues (Memory, Network, Async, Database, CPU blocking)

🧮 Calculates a Production Stability Score

🤖 Uses Copilot CLI to generate root cause explanations and fix suggestions

Instead of manually scanning thousands of log lines, you can now run:

ai-debug analyze logs.txt --env=prod

And get structured output like:

⚠️ Detected Issues:

1. Possible Memory Leak

   • Heap usage growth detected
   • Redis connection not properly closed

2. Unhandled Promise Rejection

   • payment.service.js:84

3. Event Loop Blocking Risk

   • Synchronous crypto operation detected

Production Stability Score: 72%

This project combines log analysis + AI-powered reasoning directly in the terminal — where DevOps workflows actually happen.

Demo

CLI Output

Interactive AI Suggestions

My Experience with GitHub Copilot CLI

Copilot CLI helped me quickly generate root cause explanations and actionable fixes for detected issues.
While Windows requires interactive mode, using WSL/Linux allowed fully automated AI-assisted debugging.

GitHub Repo