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https://github.com/murdercode/maisquelle

🌽 Optimize your MySQL database configuration with AI
https://github.com/murdercode/maisquelle

mariadb mysql performance sysadmin

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🌽 Optimize your MySQL database configuration with AI

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README 

        
# MaisQuelle 🌽 Your AI-Powered MySQL companion



**MaisQuelle** (_**M**ySQL **A**rtificial **I**ntelligence **S**ystem for **Q**uerying, **U**nderstanding, **E**

valuating, **L**earning and **L**og **E**nhancement_) is a smart configurator and performance monitoring tool that

combines the power of artificial intelligence with traditional monitoring techniques to keep your MySQL servers happy

and healthy! 🎯



> ⚠️ WARNING: MaisQuelle is currently in an experimental phase and is NOT ready for production use!



Inspired by the versatility of [MySQLTuner](https://github.com/major/MySQLTuner-perl) and its essential role in MySQL

administration, MaisQuelle aims to bring that

same level of utility to performance monitoring and optimization, enhanced with AI capabilities.





MaisQuelle Animated Demo



## Why MaisQuelle? 🤔



- 🧠 AI-Enhanced Analysis: Uses machine learning algorithms to provide intelligent insights and recommendations for your

  MySQL performance

- 📊 Smart Reporting: Automatically generates human-readable reports with AI-driven explanations

- 🎯 Predictive Monitoring: Identifies potential issues before they become problems

- 🚀 Performance Optimization: Provides AI-powered suggestions for query optimization and system tuning

- 🤖 Self-Learning: Continuously improves its recommendations based on your system's specific patterns



## Requirements



- Python 3.6+

- MySQL Server 5.7+ or MariaDB 10.2+

- [Anthropic API Key](https://www.anthropic.com/) (for AI-enhanced features)



## Installation



1. Clone the repository:

   ```bash

   git clone https://github.com/murdercode/maisquelle.git

   cd maisquelle

   ```



2. Install required dependencies:

   ```bash

   pip install -r requirements.txt

   ```



3. Configure settings:

    - Copy `settings.example.yaml` to `settings.yaml`

    - Add your Anthropic API key and MySQL configuration in `settings.yaml`



## Configuration



MaisQuelle can be configured in two ways:



1. Using `settings.yaml`:



```yaml

mysql:

  host: localhost

  user: root

  password: ""

  port: 3306



monitoring:

  level: 2  # 1-Basic, 2-Advanced (default), 3-Expert

  interval: 300



anthropic:

  api_key: "your-api-key-here"

```



2. Using command-line arguments (these override settings.yaml):



```bash

# Basic monitoring

python maisquelle.py --level 1 --host localhost --port 3306



# Advanced monitoring (default)

python maisquelle.py --level 2 -u root -p password



# Expert monitoring with all features

python maisquelle.py --level 3 --enable-tables

```



### Available Arguments



- `--level`: Monitoring detail level (1=Basic, 2=Advanced, 3=Expert)

- `--host`: MySQL host address (default: localhost)

- `-u, --user`: MySQL username (default: root)

- `-p, --password`: MySQL password (default: empty)

- `--port`: MySQL port number (default: 3306)

- `--enable-tables`: Enable detailed table statistics collection



## Monitoring Levels



### Level 1: Basic Health Check 🟢



- System resources (CPU, RAM, Disk)

- MySQL service status

- Basic MySQL metrics

- Essential health indicators

- Perfect for daily monitoring



### Level 2: Advanced Analysis 🟡



Everything in Level 1, plus:



- Query cache analysis

- InnoDB metrics

- Slow query detection

- Performance schema basics

- Ideal for weekly performance reviews



### Level 3: Expert Inspection 🔴



Everything in Level 2, plus:



- Detailed table statistics

- Index analysis

- Deep performance metrics

- Complete schema inspection

- Recommended for monthly deep analysis



## Features



### System Monitoring



- CPU utilization and specifications

- Memory usage (RAM and swap)

- Disk space statistics



### MySQL Monitoring



- Service status and processes

- Server variables and status

- Query cache analysis

- InnoDB metrics

- Slow query analysis

- Performance schema metrics

- Table statistics (optional)



### AI-Enhanced Features



- Performance optimization recommendations based on monitoring level

- Intelligent query analysis

- Interactive command suggestions

- Automated improvement execution

- Level-specific insights and recommendations



## Output



Reports are generated in the `logs` directory with timestamps:



```

logs/status_YYYYMMDD_HHMMSS.txt

```



### Report Sections



1. **Monitoring Level Information**

    - Current level details

    - Enabled features

    - AI analysis depth



2. **System Resources**

    - CPU metrics

    - Memory usage

    - Disk statistics



3. **MySQL Status**

    - Process information

    - Service status

    - Server variables



4. **Performance Metrics** (Level 2+)

    - Query cache analysis

    - InnoDB metrics

    - Slow queries

    - Performance schema data



5. **Detailed Analytics** (Level 3)

    - Table statistics

    - Index analysis

    - Deep performance metrics



6. **AI Optimization**

    - Level-specific recommendations

    - Suggested improvements

    - Execution results



## Best Practices



1. **Monitoring Level Selection**

    - Use Level 1 for daily health checks

    - Use Level 2 for weekly performance reviews

    - Use Level 3 for monthly deep analysis

    - Avoid Level 3 during peak hours



2. **Configuration**

    - Use `settings.yaml` for persistent configuration

    - Override with CLI arguments when needed

    - Configure appropriate permissions



3. **Security**

    - Store API keys securely

    - Use encrypted connections

    - Regularly rotate credentials



## Troubleshooting



### Common Issues



1. **Settings Loading**

    - Ensure `settings.yaml` exists

    - Check YAML syntax

    - Verify file permissions



2. **MySQL Connection**

    - Confirm MySQL server is running

    - Verify credentials

    - Check port availability



3. **AI Features**

    - Validate Anthropic API key

    - Check internet connectivity

    - Monitor API rate limits



## Contributing



1. Fork the repository

2. Create your feature branch (`git checkout -b feature/AmazingFeature`)

3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)

4. Push to the branch (`git push origin feature/AmazingFeature`)

5. Open a Pull Request



## License



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



## Author



Your Name



- GitHub: [@murdercode](https://github.com/murdercode)

- Email: [email protected]