AI-Powered Natural Language Log Analyzer

This blog post is a brief documentation of my journey for Google Summer Of Code – 2025 with the Fedora Community.

About Me:

Name: Tanvi Ruhika

e-Mail: tanviruhika1217@gmail.com

A 1st year Computer Science (Core) student at GITAM University, India. I’ve always loved building things that feel futuristic yet genuinely useful ,whether it’s a gesture-controlled robot, a voice-activated smart house, or an AI tool that speaks human. My core interests lie in artificial intelligence, automation, and developing tools that make technology more intuitive and accessible for developers.

I’m also drawn to creativity and design, and I’m always excited by projects that blend technology with a touch of personality. I’ve always looked for ways to expose myself to new opportunities and technologies, and Google Summer of Code felt like the perfect chance to do just that. When I got selected, I knew I wanted to give it my all ,not just to build something meaningful, but to truly dive deeper into the world of open source.

Project Abstract
ExplainMyLogs is an innovative tool designed to transform complex system and application logs
into clear, concise natural language explanations. This project aims to leverage large language
models and machine learning techniques to help developers and DevOps engineers quickly
identify, understand, and resolve issues within their infrastructure. By translating cryptic log
entries into human-readable explanations and actionable insights, ExplainMyLogs will
significantly reduce debugging time and lower the barrier to entry for infrastructure
troubleshooting.

Project Goals

Enable progressive learning from user feedback to improve analysis accuracy.

Develop a log parser capable of handling various log formats from common services.

Create an AI-powered analysis engine that identifies patterns, anomalies, and potential
issues in log data.

Build a natural language generator that produces clear explanations of detected issues.

Implement a command-line interface for easy integration into existing workflows.

Design a simple web interface for interactive log analysis and visualization.

Provide actionable recommendations for resolving identified issues.

Timeline

The timeline of the project goes like this:

WEEK-1

Hugging face -LLM Course

Fedora Linux Terminal Commands