Incident Management with LLMs

This repo is co-authored by Markus Rollwagen and Luca Perrozzi.

This repository contains a Jupyter notebook demonstrating how Large Language Models (LLMs) can be used to support incident management processes in IT operations.

Overview

The notebook explores the application of LLMs, specifically Claude models, to enhance various aspects of incident management:

• Incident classification
• Root cause analysis
• Solution recommendation
• Knowledge base querying

Contents

• Incident-Management-supported-by-LLMs.ipynb: The main Jupyter notebook containing the code and explanations.

Key Features

• Incident Classification: Utilizes LLMs to categorize incidents based on their descriptions[1].
• Root Cause Analysis: Employs LLMs to identify potential root causes of incidents[1].
• Solution Recommendation: Leverages LLMs to suggest possible solutions for incidents[1].
• Knowledge Base Integration: Demonstrates how to use LLMs to query a knowledge base for relevant information[1].

Requirements

• Python 3.x
• Jupyter Notebook
• AWS tokens
• Required Python libraries (listed in the notebook)

Usage

1. Clone this repository
2. Install the required dependencies
3. Open and run the Jupyter notebook

Contributing

Contributions, issues, and feature requests are welcome. Feel free to check the issues page if you want to contribute.

License

MIT