I Built an AI Tool That Analyzes Production Logs and Generates Incident Reports

Luke Xue — Thu, 12 Mar 2026 08:41:18 +0000

In many production incidents, the first thing engineers do is open logs and start searching for errors.

But in reality:

Logs are huge
Error chains are messy
Root causes are often hidden
And writing incident reports takes time

So I built a small tool to experiment with a simple idea:

What if logs could automatically turn into incident analysis reports?

The Idea

During incident response, engineers usually try to answer questions like:

What is the root cause?
When did the errors start?
How severe is the incident?
Which services are affected?
What should we do next?

All of these answers already exist inside the logs.

The problem is that extracting them takes time.

So I built an open-source project that:

Turns raw logs into a structured incident report.

Paste logs → get analysis.

Live Demo

You can try it here:

👉 Live Demo

http://116.233.96.74:8025

Just paste logs and click Analyze.

Example log:

2026-03-08 15:05:09 ERROR OrderService
java.lang.NullPointerException

2026-03-08 15:05:10 ERROR PaymentService
Timeout while calling downstream service

2026-03-08 15:05:11 ERROR OrderController
BusinessException: order not found

The system automatically generates an incident report.

What the Tool Generates

Instead of raw logs, the system produces structured insights.

Example output:

Incident Severity

P3

Recommended Action

Observe system metrics

Root Cause Signals

Possible downstream timeout
Possible null pointer issue

Incident Timeline

15:05:09 ERROR OrderService
15:05:10 ERROR PaymentService
15:05:11 ERROR OrderController

Error Trend

Shows how errors increase over time.

Service Impact

Identifies which service is affected.

Why I Built This

Most incident analysis tools focus on:

monitoring
alerts
dashboards

But the actual debugging still happens in logs.

So I wanted to experiment with a system that focuses on:

logs → insights → incident report

Instead of just storing logs.

Architecture

The demo is intentionally simple.

Browser
   ↓
Nginx (static demo page)
   ↓
Spring Boot API
   ↓
Log Analyzer
   ↓
Incident Insight

The backend performs several steps:

Log preprocessing
Root cause signal extraction
Error pattern detection
Timeline generation
Incident report assembly

Key Features

Current open-source version includes:

Root cause signal detection
Incident timeline generation
Error trend analysis
Service impact estimation
Incident report generation
Markdown / HTML / PDF export

Example Incident Report

Instead of manually writing a post-mortem, the system generates:

Executive Summary
Root Cause Analysis
Incident Timeline
Error Trend
Service Impact
Short-term Improvements
Long-term Improvements

GitHub Repository

The project is open source.

👉 GitHub

https://github.com/YOUR_REPO

If you're interested in DevOps / SRE tooling, feel free to check it out.

What I'm Exploring Next

Some ideas I'm experimenting with:

AI-powered root cause analysis
cross-service incident correlation
automatic incident report generation
integration with observability systems

Feedback Welcome

This is still an early experiment.

If you work with logs, SRE, or incident response, I would love to hear your feedback.

⭐ If you like the idea, consider starring the project on GitHub.

And if you'd like to try it: