Automated Log Analyzer & Error Detection System

Overview

The Automated Log Analyzer is a lightweight web application that helps analyze server log files and categorize log entries into Errors, Warnings, and Informational messages.

This tool is useful for system monitoring, debugging, and troubleshooting, which are important tasks in Site Reliability Engineering (SRE) and IT Operations roles.

The application allows users to upload a log file and automatically processes it to identify critical issues in the system logs.

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Key Features

• Upload and analyze server log files
• Automatic detection of ERROR, WARNING, and INFO log messages
• Simple and clean web-based dashboard
• Organized display of log results for easy debugging
• Lightweight and fast log parsing
• Beginner-friendly monitoring tool for infrastructure logs

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Technologies Used

Programming Language

• Python

Backend Framework

• Flask

Frontend

• HTML5
• CSS3

Tools

• Git
• GitHub
• VS Code

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Project Structure

log-analyzer
│
├── main.py
├── requirements.txt
├── Procfile
├── runtime.txt
│
├── templates
│   └── index.html
│
├── static
│   └── style.css
│
└── uploads

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File Description

main.py

Contains the Flask application and the log analysis logic.

requirements.txt

Lists Python dependencies required to run the application.

templates/index.html

Frontend page for uploading log files and displaying results.

static/style.css

Contains styling for the user interface.

uploads/

Stores uploaded log files temporarily for analysis.

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How the System Works

1. The user uploads a log file through the web interface.
2. The backend Flask application reads the log file.
3. The system scans each line of the file.
4. Log entries are categorized based on keywords:
   • ERROR
   • WARNING
   • INFO
5. The categorized logs are displayed on the web dashboard.

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Log Analysis Logic

The analyzer checks each line of the uploaded log file and classifies entries using simple keyword detection.

Log Keyword	Category
ERROR	Critical system error
WARNING	Potential issue
INFO	General system information

This helps quickly identify problems in system logs.

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Example Log File

Example of a log file that can be analyzed:

INFO Server started
INFO User logged in
WARNING Memory usage high
ERROR Database connection failed
INFO Request processed
ERROR Timeout error

After analysis, the system will separate the logs into different categories.

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How to Run the Project Locally

1. Clone the Repository

git clone https://github.com/yourusername/automated-log-analyzer.git

2. Navigate to the Project Folder

cd automated-log-analyzer

3. Install Dependencies

pip install -r requirements.txt

4. Run the Application

python main.py

5. Open the Web Application

Open the browser and go to:

http://localhost:10000

Upload a log file to start analyzing logs.

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Use Cases

This tool can be used for:

• Server log analysis
• Application debugging
• System monitoring
• Learning basic log analysis techniques
• Understanding SRE monitoring concepts

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Future Improvements

Possible enhancements for the project include:

• Real-time log monitoring
• Log search functionality
• Error statistics dashboard
• Graph visualization of log data
• Support for large log files
• Alert notification system

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Author

Saurabh Kishan Butale

Computer Engineering Student
Interested in Software Development, Monitoring Systems, and Cloud Applications.

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License

This project is for educational and demonstration purposes.

© All Rights Reserved
Copyright Saurabh Kishan Butale 2026