datadog-monitor-deployer 0.1.0

A powerful tool for managing Datadog monitors as code

Datadog Monitor Deployer

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A powerful and flexible tool for managing Datadog monitors as code. This project enables teams to define, deploy, and manage Datadog monitors using a declarative approach, supporting both YAML/JSON configurations and Python classes.

🌟 Key Features

• 📝 Multiple Definition Formats:
  • YAML/JSON with schema validation
  • Python classes for programmatic creation
  • Hybrid approach supporting both methods
• 🔍 Comprehensive Monitor Type Support:
  • Metric monitors
  • Event monitors
  • Log monitors
  • APM monitors
  • Network monitors
  • Process monitors
• ⚡ Advanced Functionality:
  • Robust alerting configuration
  • Multiple notification channels (Email, Slack, PagerDuty)
  • Custom message templates
  • Tagging and organization
  • Full CRUD operations
• 🛡️ Enterprise-Ready:
  • Idempotent operations
  • Comprehensive testing
  • Secure authentication handling
  • CI/CD pipeline integration

🚀 Quick Start

1. Install the package:

pip install datadog-monitor-deployer

2. Set up your Datadog credentials:

export DD_API_KEY="your-api-key"
export DD_APP_KEY="your-app-key"

3. Create a monitor definition (example.yaml):

monitors:
  - name: "High CPU Usage Alert"
    type: "metric alert"
    query: "avg(last_5m):avg:system.cpu.user{*} > 80"
    message: "CPU usage is above 80%"
    tags:
      - "env:production"
      - "service:web"
    options:
      notify_no_data: true
      evaluation_delay: 900

4. Deploy your monitor:

dd-monitor deploy example.yaml

📚 Documentation

For detailed documentation, visit our Documentation Site.

• Getting Started Guide
• Configuration Reference
• API Documentation
• CLI Reference
• Best Practices

🛠️ Development Setup

1. Clone the repository:

git clone https://github.com/fleXRPL/datadog-monitor-deployer.git
cd datadog-monitor-deployer

2. Create and activate a virtual environment:

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

3. Install development dependencies:

pip install -r requirements-dev.txt

4. Run tests:

pytest

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

📄 License

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

🔒 Security

Please review our Security Policy for reporting security vulnerabilities.

📊 Project Status

This project is actively maintained and used in production environments. For the latest updates, see our Changelog.

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Built with ❤️ by the fleXRPL team