https://github.com/peandaddy/sqlmonlit
A modular, extensible, and production-ready Streamlit application for real-time monitoring of SQL Server instances.
https://github.com/peandaddy/sqlmonlit
sqlmonitor sqlserver streamlit-dashboard
Last synced: 10 months ago
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A modular, extensible, and production-ready Streamlit application for real-time monitoring of SQL Server instances.
- Host: GitHub
- URL: https://github.com/peandaddy/sqlmonlit
- Owner: peandaddy
- License: other
- Created: 2025-03-26T00:22:41.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-03-26T02:14:14.000Z (10 months ago)
- Last Synced: 2025-03-26T03:23:26.513Z (10 months ago)
- Topics: sqlmonitor, sqlserver, streamlit-dashboard
- Language: Python
- Homepage:
- Size: 2.27 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# SQLMonLit - SQL Monitoring Dashboard
A modular, extensible, and production-ready `Streamlit` application for real-time monitoring of SQL Server instances. This dashboard fetches and displays key performance metrics (**CPU, Memory, TempDB, Disk, Backup, and Activity**) from multiple SQL Server instances, leveraging stored procedures for data retrieval.
## Features
- **Multi-Instance Support**: Monitor multiple SQL Server instances configured via `config.ini`.
- **Real-Time Updates**: Auto-refresh every `60` seconds with a manual refresh option.
- **Tabular UI**: Organized metrics in tabs (CPU, Memory, TempDB, Disk, Backup, Activity) with timestamped entries.
- **Data Limiting**: Retains up to 10 recent records per metric, preventing overload.
- **Duplicate Prevention**: Ensures no duplicate records during rapid updates.
- **Modular Design**: Separates configuration, database logic, UI, and app orchestration for maintainability and scalability.
- **Error Handling**: Graceful handling of connection and query failures with user feedback.
## Project Structure
```
sqlmonlit/
├── app.py # Main application logic and orchestration
├── config.py # Configuration loading and management
├── database.py # Database connection and data fetching logic
├── ui.py # Streamlit UI components and rendering
├── config.ini # Sample configuration file (edit with your DB details)
├── requirements.txt # Python dependencies
└── README.md # This file
```
## Prerequisites
- **Python**: 3.8 or higher
- **SQL Server**: Accessible instances with the following stored procedures:
- `usp_SQLMonLit_CPU`
- `usp_SQLMonLit_Memory`
- `usp_SQLMonLit_Tempdb`
- `usp_SQLMonLit_Batch`
- `usp_SQLMonLit_Activity`
- **Dependencies**: Listed in `requirements.txt`
## Installation
1. **Clone the Repository**:
```bash
git clone https://github.com/peandaddy/sqlmonlit.git
cd sqlmonlit
```
2. **Set Up a Virtual Environment (recommended)**:
```python
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. **Install Dependencies**:
```python
pip install -r requirements.txt
```
4. **Configure config.ini**:
* Copy the sample `config.ini` and edit it with your SQL Server credentials:
```ini
[database1]
host=your_sql_server_host
user=your_username
password=your_password
database=your_database_name
[database2]
host=another_sql_server_host
user=another_username
password=another_password
database=another_database_name
```
* Add as many `[databaseX]` sections as needed.
## Usage
1. Run the Application:
```bash
streamlit run app.py
```
2. Interact with the Dashboard:
* Select an instance from the sidebar.
* View metrics in the tabs (`auto-refreshes every 60 seconds`).
* Use buttons: "`Refresh Now`" (manual update), "`Stop`" (pause monitoring), "`Clear`" (reset data).
## Configuration
* Edit `config.ini`: Modify instance details (host, user, password, database).
* Customize Metrics: Update `SQLMonitorDB.METRICS` in `database.py` to add or change stored procedures.
* Refresh Interval: Adjust the `60` in `app.py` **`current_time - st.session_state["last_update"] >= 60`** to change the auto-refresh timing.
## Development
### Adding New Metrics
1. Add the metric key and stored procedure to `SQLMonitorDB.METRICS` in `database.py`.
2. Update `render_dashboard` in `ui.py` to display the new metric in a tab.
### Testing
1. Install `pytest`:
```python
pip install pytest
```
2. Write tests in a `tests/` directory (not included) to validate `config.py`, `database.py`, etc.
## Contributing
Contributions are welcome!
## License
These samples and templates are all licensed under the MIT license. See the `LICENSE` file in the root.
## Author
* Ji Wang - https://github.com/peandaddy
Created to demonstrate advanced Python, Streamlit, and SQL Server monitoring skills. Contact me for collaboration or inquiries!
## Acknowledgments
* Built with `Streamlit` and `pymssql`.
* Inspired by the need for robust SQL Server monitoring tools.