🔍 Log Analytics Tool

🚀 Professional Log Analysis Tool for ISP & Office Environments

A powerful, web-based log analysis application designed for ISP and office environments. Built with modern web technologies to provide comprehensive log parsing, analysis, and visualization capabilities.

📋 Table of Contents

✨ Features
🚀 Quick Start
📖 Usage Guide
🎯 Supported Log Formats
💻 Technology Stack
📁 Project Structure
🔧 Configuration
🚢 Deployment
🤝 Contributing
📋 Changelog
🐛 Troubleshooting
📞 Support
📜 License

✨ Features

🔧 Core Functionality

📁 Multiple Input Methods: Upload log files or paste content directly
🧠 Intelligent Format Detection: Automatic recognition of Apache, Nginx, Syslog, and custom formats
⚡ Real-time Processing: Instant analysis with live progress updates
📊 Export Capabilities: Download results in CSV, JSON, TXT formats
📱 Responsive Interface: Optimized for desktop, tablet, and mobile devices

📊 Analysis Engine

📈 Statistical Overview: Entry counts, error rates, format detection
🌐 IP Intelligence: Top client IPs and geographic distribution (web logs)
📊 HTTP Analytics: Status code distribution and trends (web logs)
🔗 URL Analytics: Most requested endpoints and patterns (web logs)
🖥️ System Monitoring: Hostname tracking and process analysis (syslog)

🎨 User Experience

💫 Modern UI/UX: Clean, professional design with intuitive navigation
🌓 Dark/Light Theme: Adaptive theming for comfortable viewing
📊 Interactive Visualizations: Charts and graphs for better insights
🎯 Drag & Drop: Seamless file upload experience
⏳ Progress Indicators: Real-time feedback during processing

🛡️ Security & Performance

🔒 Secure File Handling: Safe processing of uploaded files with size limits
🧠 Memory Efficient: Optimized parsing for large log files (50MB+ support)
🛠️ Error Handling: Comprehensive error reporting and recovery
✅ Input Validation: Robust validation for all input types
🌐 Cross-Platform: Compatible with Windows, macOS, and Linux

🚀 Quick Start

📋 Prerequisites

Python 3.7+ 🐍
Modern web browser 🌐
100MB+ free disk space 💾

⚡ Installation & Setup

🚀 Option 1: Quick Start (Recommended)

# Clone the repository
git clone <repository-url>
cd log-analytics

# Create virtual environment
python -m venv log_analytics_venv
source log_analytics_venv/bin/activate  # Windows: log_analytics_venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Launch application
python app.py

# Open browser and navigate to:
# http://localhost:5000

🐳 Option 2: Docker (Alternative)

# Build Docker image
docker build -t log-analytics .

# Run container
docker run -p 5000:5000 log-analytics

# Access at: http://localhost:5000

📦 Option 3: Production Deployment

# Using Gunicorn (Recommended for production)
pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 app:app

# Access at: http://your-server:5000

📖 Usage Guide

📁 File Upload Method

📂 Select Upload Option: Click the file upload area or drag files directly
📋 File Requirements: Supports .log, .txt formats (max 50MB)
🚀 Initiate Processing: Click "Analyze Logs" to begin parsing
📊 View Dashboard: Explore results across multiple analysis tabs

✏️ Direct Input Method

📝 Select Text Input: Choose "Paste logs directly" option
📋 Content Entry: Paste log content in the provided text area
⚡ Process Data: Click "Analyze Logs" for immediate processing
📈 Review Results: Examine analysis across all available views

📊 Analysis Results Overview

📈 Summary Dashboard

📊 Total log entries processed
🚨 Error and warning counts
🔍 Detected log format information
⏰ Processing timestamp and metadata

🌐 Network Intelligence (Web Logs)

🔝 Top IP Addresses: Most active client IPs with request counts
🗺️ Geographic Data: Country/region distribution (if available)
📈 Access Patterns: Peak usage times and trends

📊 HTTP Analytics (Web Logs)

📊 Status Code Distribution: 2xx, 3xx, 4xx, 5xx response breakdown
⚡ Performance Metrics: Response time analysis
🚨 Error Tracking: Failed request patterns and sources

🎯 Supported Log Formats

Format	Description	Use Case
🌐 Apache	Standard web server access logs	Web traffic analysis
🌐 Nginx	HTTP server logs with configurable formatting	Load balancer logs
💻 Syslog	Standard system logging protocol	System monitoring
🛜 MikroTik	RouterOS firewall and system logs	ISP network devices
🌐 Cisco IOS	Router and switch logs	Enterprise networking
🛜 Juniper	Firewall and routing platform logs	Network infrastructure

📝 Log Format Examples

Apache Access Log

192.168.1.100 - - [10/Oct/2023:13:55:36 +0000] "GET /api/users HTTP/1.1" 200 1234 "-" "Mozilla/5.0"

Syslog Entry

Oct 10 13:55:36 server1 sshd[12345]: Failed password for invalid user admin from 192.168.1.100 port 22 ssh2

💻 Technology Stack

Core Technologies

Key Dependencies

🔗 Flask: Web framework for Python
⚙️ Werkzeug: WSGI utility library
📊 Python Standard Library: Built-in modules for file handling, regex, etc.

Development Tools

📁 Project Structure

log-analytics/
├── 📄 app.py                    # 🚀 Main Flask application
├── 📄 requirements.txt          # 📦 Python dependencies
├── 📄 README.md                 # 📚 Project documentation
├── 📄 LICENSE                   # 📜 MIT license file
├── 📄 .gitignore               # 🚫 Git ignore patterns
├── 📁 templates/               # 🎨 HTML templates
│   └── index.html              # 🌐 Main web interface
├── 📁 static/                  # 🎨 Static assets
│   ├── styles.css              # 💅 Application styling
│   └── script.js               # ⚡ Frontend functionality
├── 📁 uploads/                 # 📁 Log files (auto-generated)
└── 📁 __pycache__/             # 🐍 Python bytecode (auto-generated)

🔧 Configuration

Application Settings

# Default Configuration (app.py)
PORT = 5000
MAX_FILE_SIZE = 50 * 1024 * 1024  # 50MB
UPLOAD_FOLDER = 'uploads'
SECRET_KEY = 'your-secret-key-here'  # Change in production

Environment Variables

export FLASK_ENV=production
export SECRET_KEY=your-production-secret
export PORT=8080

🚢 Deployment

🖥️ Development Deployment

# Using Flask development server
python app.py

# Access at: http://localhost:5000

🏭 Production Deployment

Option A: Gunicorn (Recommended)

# Install Gunicorn
pip install gunicorn

# Run with multiple workers
gunicorn -w 4 -b 0.0.0.0:5000 app:app

# Access at: http://your-server:5000

Option B: Docker Deployment

FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 5000
CMD ["python", "app.py"]

# Build and run
docker build -t log-analytics .
docker run -p 5000:5000 log-analytics

🤝 Contributing

We welcome contributions from the community! 🌟

🚀 Getting Started

🍴 Fork the repository
🌿 Create a feature branch: git checkout -b feature/amazing-feature
💻 Make your changes
✅ Test thoroughly
📤 Submit a pull request

📋 Contribution Guidelines

📝 Follow PEP 8 style guidelines for Python code
🧪 Write comprehensive tests for new features
📚 Update documentation for API changes
📱 Ensure responsive design for UI modifications
🔄 Maintain backward compatibility when possible

🎯 Areas for Contribution

🔧 New Log Format Support: Additional network devices or applications
📊 Enhanced Analytics: New visualization types or analysis methods
⚡ Performance Improvements: Memory usage, processing speed
💫 UI/UX Enhancements: Accessibility, mobile optimization
🧪 Testing: Unit tests, integration tests, performance benchmarks

📋 Changelog

🆕 Version 1.0.0 (Current)

✨ Initial release with core log analysis functionality
🌐 Support for Apache, Nginx, and Syslog formats
📱 Modern responsive web interface
📊 Export capabilities (CSV, JSON, TXT)
⚡ Real-time processing with progress indicators

🔮 Planned Features

💾 Database integration for result persistence
🔍 Advanced filtering and search capabilities
🚀 API endpoints for programmatic access
🌍 Multi-language support
🔌 Plugin system for custom log formats

🐛 Troubleshooting

❌ Common Issues

Problem	Solution
Application won't start	Verify Python 3.7+ is installed, check if port 5000 is available
File upload fails	Confirm file size is under 50MB limit, check upload directory permissions
Memory errors with large files	Increase system memory allocation, process files in smaller chunks
Slow processing times	Enable async processing for large files, optimize regex patterns

🔧 Getting Help

📖 Check this README thoroughly
🔍 Search existing GitHub issues
💬 Create a new issue with detailed information
📧 Contact: work.rezaul@outlook.com

📞 Support & Contact

💬 Get Help

📧 Email: work.rezaul@outlook.com
🐛 Issues: Create a GitHub issue
💭 Discussions: GitHub Discussions

🌟 Show Your Support

⭐ Star this project if you find it helpful
🐛 Report bugs to help improve the tool
💡 Suggest features for future releases
📖 Share with others who might benefit

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

MIT License

Copyright (c) 2023 REZ LAB

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

👨‍💻 Author & Contact

Rezaul Karim

🏢 REZ LAB

🎯 About This Project

Built with ❤️ for ISP and office environments

⭐ If you find this project helpful, please give it a star!

✨ Features • 🚀 Quick Start • 📖 Usage • 🤝 Contribute

🌟 Key Features

🔧 Core Functionality

Multiple Input Methods: Upload log files or paste content directly
Intelligent Format Detection: Automatic recognition of Apache, Nginx, Syslog, and custom formats
Real-time Processing: Instant analysis with live progress updates
Export Capabilities: Download results in CSV, JSON formats
Responsive Interface: Optimized for desktop, tablet, and mobile devices

📊 Analysis Engine

Statistical Overview: Entry counts, error rates, format detection
IP Intelligence: Top client IPs and geographic distribution (web logs)
HTTP Analytics: Status code distribution and trends (web logs)
URL Analytics: Most requested endpoints and patterns (web logs)
System Monitoring: Hostname tracking and process analysis (syslog)

🎨 User Experience

Modern UI/UX: Clean, professional design with intuitive navigation
Dark/Light Theme: Adaptive theming for comfortable viewing
Interactive Visualizations: Charts and graphs for better insights
Drag & Drop: Seamless file upload experience
Progress Indicators: Real-time feedback during processing

🛡️ Security & Performance

Secure File Handling: Safe processing of uploaded files with size limits
Memory Efficient: Optimized parsing for large log files (50MB+ support)
Error Handling: Comprehensive error reporting and recovery
Input Validation: Robust validation for all input types
Cross-Platform: Compatible with Windows, macOS, and Linux

🚀 Quick Start Guide

Prerequisites

Python 3.7 or higher
Modern web browser
100MB+ free disk space for log processing

Installation & Setup

Clone the Repository

git clone <repository-url>
cd log-analytics

Create Virtual Environment (Recommended)

python -m venv log_analytics_venv
source log_analytics_venv/bin/activate  # On Windows: log_analytics_venv\Scripts\activate

Install Dependencies
```
pip install -r requirements.txt
```
Launch Application
```
python app.py
```
Access Web Interface
```
Open: http://localhost:5000
```

📖 Usage Guide

File Upload Method

Select Upload Option: Click the file upload area or drag files directly
File Requirements: Supports .log, .txt formats (max 50MB)
Initiate Processing: Click "Analyze Logs" to begin parsing
View Dashboard: Explore results across multiple analysis tabs

Direct Input Method

Select Text Input: Choose "Paste logs directly" option
Content Entry: Paste log content in the provided text area
Process Data: Click "Analyze Logs" for immediate processing
Review Results: Examine analysis across all available views

Analysis Results Overview

📈 Summary Dashboard

Total log entries processed
Error and warning counts
Detected log format information
Processing timestamp and metadata

🌐 Network Intelligence (Web Logs)

Top IP Addresses: Most active client IPs with request counts
Geographic Data: Country/region distribution (if available)
Access Patterns: Peak usage times and trends

📊 HTTP Analytics (Web Logs)

Status Code Distribution: 2xx, 3xx, 4xx, 5xx response breakdown
Performance Metrics: Response time analysis
Error Tracking: Failed request patterns and sources

🔗 Content Analysis (Web Logs)

Popular Endpoints: Most requested URLs and resources
Content Types: Distribution of served file types
Referral Analysis: Traffic source breakdown

🖥️ System Monitoring (Syslog)

Hostname Tracking: System activity by host
Process Analysis: Application and service monitoring
Security Events: Authentication and access pattern review

🎯 Supported Log Formats

Web Server Logs

Apache HTTP Server: Standard access logs with Common/Combined formats
Nginx: HTTP server logs with configurable formatting
IIS: Microsoft Internet Information Services logs

Network Infrastructure Logs

MikroTik RouterOS: Firewall, DHCP, wireless, and system logs
Cisco IOS/XE: Router and switch logs with process information
Juniper Junos: Firewall and routing platform logs
Ubiquiti UniFi: Wireless access point and network logs

System & Security Logs

Syslog (RFC 5424): Standard system logging protocol
Windows Event Logs: System, security, and application events
Linux Audit Logs: Security and compliance monitoring
Custom Formats: Extensible parser for proprietary formats

🔧 Technical Configuration

Application Settings

# Default Configuration (app.py)
PORT = 5000
MAX_FILE_SIZE = 50 * 1024 * 1024  # 50MB
UPLOAD_FOLDER = 'uploads'
SECRET_KEY = 'your-secret-key-here'  # Change in production

Environment Variables

export FLASK_ENV=production
export SECRET_KEY=your-production-secret
export PORT=8080

📁 Project Architecture

log-analytics/
├── 📄 app.py                    # Main Flask application
├── 📄 requirements.txt          # Python dependencies
├── 📄 README.md                 # Project documentation
├── 📄 LICENSE                   # MIT license file
├── 📄 .gitignore               # Git ignore patterns
├── 📁 templates/               # HTML templates
│   └── index.html              # Main web interface
├── 📁 static/                  # Static assets
│   ├── styles.css              # Application styling
│   └── script.js               # Frontend functionality
├── 📁 uploads/                 # Log files (auto-generated)
└── 📁 __pycache__/             # Python bytecode (auto-generated)

🛠️ Development & Extension

Adding New Log Formats

Extend Parser Class: Modify LogAnalyzer in app.py
Define Format Rules: Add regex patterns and parsing logic
Create Analysis Methods: Implement format-specific analytics
Update UI: Add format selection and result visualization

Customizing the Interface

Template Modification: Edit templates/index.html
Styling Updates: Modify static/styles.css
JavaScript Enhancement: Extend static/script.js
Responsive Design: Ensure mobile compatibility

Performance Optimization

Memory Management: Efficient handling of large log files
Caching Strategy: Redis integration for repeated analyses
Database Integration: PostgreSQL for result persistence
Async Processing: Background job processing for large files

📝 Log Format Examples

Apache Access Log

192.168.1.100 - - [10/Oct/2023:13:55:36 +0000] "GET /api/users HTTP/1.1" 200 1234 "-" "Mozilla/5.0"
192.168.1.101 - - [10/Oct/2023:13:55:37 +0000] "POST /api/login HTTP/1.1" 401 567 "-" "curl/7.68.0"

Syslog Entry

Oct 10 13:55:36 server1 sshd[12345]: Failed password for invalid user admin from 192.168.1.100 port 22 ssh2
Oct 10 13:55:37 server2 kernel: [12345.678901] USB device disconnected

Cisco IOS Log

*Oct 10 13:55:36.123: %LINEPROTO-5-UPDOWN: Line protocol on Interface GigabitEthernet0/1, changed state to up
*Oct 10 13:55:37.456: %SECURITY-6-IPACCESSLOGP: list 100 denied tcp 192.168.1.100(12345) -> 10.0.0.1(80)

🤝 Contributing

We welcome contributions from the community! Here's how you can help:

Getting Started

Fork the repository
Create a feature branch: git checkout -b feature/amazing-feature
Make your changes
Test thoroughly
Submit a pull request

Contribution Guidelines

Follow PEP 8 style guidelines for Python code
Write comprehensive tests for new features
Update documentation for API changes
Ensure responsive design for UI modifications
Maintain backward compatibility when possible

Areas for Contribution

New Log Format Support: Additional network devices or applications
Enhanced Analytics: New visualization types or analysis methods
Performance Improvements: Memory usage, processing speed
UI/UX Enhancements: Accessibility, mobile optimization
Testing: Unit tests, integration tests, performance benchmarks

📋 Changelog

Version 1.0.0 (Current)

Initial release with core log analysis functionality
Support for Apache, Nginx, and Syslog formats
Modern responsive web interface
Export capabilities (CSV, JSON)
Real-time processing with progress indicators

Planned Features

Database integration for result persistence
Advanced filtering and search capabilities
API endpoints for programmatic access
Multi-language support
Plugin system for custom log formats

🐛 Troubleshooting

Common Issues

Application won't start

Verify Python 3.7+ is installed
Check if port 5000 is available
Ensure all dependencies are installed

File upload fails

Confirm file size is under 50MB limit
Check upload directory permissions
Verify file format is supported

Memory errors with large files

Increase system memory allocation
Process files in smaller chunks
Consider upgrading hardware

Slow processing times

Enable async processing for large files
Optimize regex patterns for better performance
Consider background processing for very large logs

📞 Support & Contact

For support, feature requests, or bug reports:

Email: work.rezaul@outlook.com
Issues: Create a GitHub issue with detailed information
Discussions: Use GitHub Discussions for questions and ideas

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

👨‍💻 Author & Contact

Author: Rezaul Karim Email: work.rezaul@outlook.com Organization: REZ LAB

🎯 Why Choose Log Analytics Tool?

Purpose-Built for ISP & Office Environments

Network-Focused: Specifically designed for ISP networks, office IT infrastructure
Multi-Format Support: Handles the diverse log formats found in real-world deployments
Practical Analytics: Focuses on actionable insights rather than academic metrics
Ease of Use: Designed for IT professionals, not just data scientists

Technical Excellence

Lightweight Architecture: Minimal resource requirements, maximum performance
Modern Tech Stack: Built with current, maintainable technologies
Extensible Design: Easy to add new log formats and analysis features
Production Ready: Includes security, error handling, and scalability considerations

Competitive Advantages

No Complex Setup: Single Python file deployment with minimal dependencies
Real-Time Processing: Instant results without lengthy batch processing
Intuitive Interface: Clean, professional UI that requires no training
Export Flexibility: Multiple format support for integration with existing tools

📋 System Requirements

Minimum Requirements

Operating System: Windows 10+, macOS 10.14+, Ubuntu 18.04+, CentOS 7+
Processor: 1 GHz dual-core (64-bit)
Memory: 2 GB RAM (4 GB recommended for large files)
Storage: 100 MB free space + log file size
Network: None required (local processing)

Recommended Specifications

Processor: 2 GHz quad-core or better
Memory: 8 GB RAM for processing 100MB+ log files
Storage: SSD for improved performance
Browser: Chrome 90+, Firefox 88+, Safari 14+, Edge 90+

Performance Scaling

Small Files (< 1MB): 1 GB RAM sufficient
Medium Files (1-10MB): 2-4 GB RAM recommended
Large Files (10-50MB): 8 GB RAM recommended
Very Large Files (>50MB): Consider file splitting or incremental processing

🚢 Deployment Guide

Development Deployment

# Clone and setup
git clone <repository-url>
cd log-analytics
python -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt

# Run development server
python app.py

Production Deployment

Using Gunicorn (Recommended)

pip install gunicorn
gunicorn -w 4 -b 0.0.0.0:5000 app:app

Using Docker

FROM python:3.9-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
EXPOSE 5000
CMD ["python", "app.py"]

docker build -t log-analytics .
docker run -p 5000:5000 log-analytics

Using Nginx + Gunicorn

server {
    listen 80;
    server_name your-domain.com;

    location / {
        proxy_pass http://127.0.0.1:5000;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

Environment Configuration

# Production environment variables
export FLASK_ENV=production
export SECRET_KEY=your-secure-secret-key-here
export PORT=5000
export MAX_FILE_SIZE=52428800  # 50MB in bytes

🔒 Security Considerations

File Upload Security

Size Limits: Maximum 50MB file uploads to prevent resource exhaustion
Format Validation: Strict file type checking before processing
Path Traversal Protection: Secure file handling prevents directory traversal
Temporary File Cleanup: Automatic cleanup of uploaded files after processing

Application Security

Secret Key Management: Use strong, unique secret keys in production
Input Sanitization: All user inputs are validated and sanitized
Error Handling: Secure error messages that don't leak system information
HTTPS Enforcement: Use reverse proxy (nginx) for SSL/TLS termination

Operational Security

Access Control: Run application with minimal required permissions
Log Security: Avoid logging sensitive information from processed files
Update Management: Keep dependencies updated for security patches
Network Security: Use firewall rules to restrict access to necessary ports

❓ Frequently Asked Questions (FAQ)

General Questions

Q: What types of log files can I analyze? A: Web server logs (Apache, Nginx, IIS), network device logs (Cisco, MikroTik, Juniper), system logs (Syslog), and custom formats.

Q: How large can the log files be? A: Up to 50MB per file. For larger files, consider splitting them or using incremental processing.

Q: Is my data stored permanently? A: No, uploaded files are processed in memory and automatically deleted after analysis. No data is persisted.

Technical Questions

Q: Can I add support for custom log formats? A: Yes! The application is designed to be extensible. See the Development section for details.

Q: Does it work on Windows? A: Absolutely! The application is cross-platform and works on Windows, macOS, and Linux.

Q: Can I integrate this with my existing monitoring tools? A: Yes, results can be exported as CSV or JSON for integration with other systems.

Troubleshooting Questions

Q: The application won't start. What should I check? A: Verify Python 3.7+ is installed, port 5000 is available, and all dependencies are installed.

Q: File uploads fail with large files. A: Check available memory and consider increasing system RAM or processing files in smaller chunks.

Q: Processing seems slow. A: Large files require more memory and processing time. Consider upgrading hardware or optimizing regex patterns.

🏆 Acknowledgments

Technologies & Libraries

Flask - Lightweight Python web framework
Jinja2 - Template engine for HTML rendering
Werkzeug - WSGI utility library
Python - Core programming language

Development Tools

Visual Studio Code - Primary development environment
Git - Version control system
Python Virtual Environments - Dependency management

Inspiration & References

Network administration communities and forums
ISP and office IT professionals who provided valuable feedback
Open source log analysis tools that inspired various features

🎯 About This Project

Built with ❤️ for ISP and office environments

REZ LAB | Email | GitHub

⭐ If you find this project helpful, please give it a star!

Name		Name	Last commit message	Last commit date
Latest commit History 18 Commits
static		static
templates		templates
.env.example		.env.example
.gitignore		.gitignore
LICENSE		LICENSE
README.md		README.md
app.py		app.py
requirements.txt		requirements.txt

License

rezaworks/Log-Analytics

Folders and files

Latest commit

History

Repository files navigation

🔍 Log Analytics Tool

📋 Table of Contents

✨ Features

🔧 Core Functionality

📊 Analysis Engine

🎨 User Experience

🛡️ Security & Performance

🚀 Quick Start

📋 Prerequisites

⚡ Installation & Setup

🚀 Option 1: Quick Start (Recommended)

🐳 Option 2: Docker (Alternative)

📦 Option 3: Production Deployment

📖 Usage Guide

📁 File Upload Method

✏️ Direct Input Method

📊 Analysis Results Overview

📈 Summary Dashboard

🌐 Network Intelligence (Web Logs)

📊 HTTP Analytics (Web Logs)

🎯 Supported Log Formats

📝 Log Format Examples

Apache Access Log

Syslog Entry

💻 Technology Stack

Core Technologies

Key Dependencies

Development Tools

📁 Project Structure

🔧 Configuration

Application Settings

Environment Variables

🚢 Deployment

🖥️ Development Deployment

🏭 Production Deployment

Option A: Gunicorn (Recommended)

Option B: Docker Deployment

🤝 Contributing

🚀 Getting Started

📋 Contribution Guidelines

🎯 Areas for Contribution

📋 Changelog

🆕 Version 1.0.0 (Current)

🔮 Planned Features

🐛 Troubleshooting

❌ Common Issues

🔧 Getting Help

📞 Support & Contact

💬 Get Help

🌟 Show Your Support

📜 License

👨‍💻 Author & Contact

🎯 About This Project

🌟 Key Features

🔧 Core Functionality

📊 Analysis Engine

🎨 User Experience

🛡️ Security & Performance

🚀 Quick Start Guide

Prerequisites

Installation & Setup

📖 Usage Guide

File Upload Method

Direct Input Method

Analysis Results Overview

📈 Summary Dashboard

🌐 Network Intelligence (Web Logs)

📊 HTTP Analytics (Web Logs)

🔗 Content Analysis (Web Logs)

🖥️ System Monitoring (Syslog)

🎯 Supported Log Formats

Web Server Logs

Network Infrastructure Logs

System & Security Logs

Packages