DataDog Dashboard Deployer

A powerful framework for deploying DataDog dashboards as code using CI/CD pipelines. Define, version, and automate your DataDog dashboard deployments using YAML configurations.

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Features

• 🚀 Configuration as Code: Define dashboards using YAML configuration files
• 🔄 Automated Deployment: Deploy dashboards automatically via GitHub Actions
• 📊 Rich Widget Support: Support for timeseries, query values, heatmaps, and more
• 🔐 Secure Credentials: Handle DataDog API credentials securely
• 🎨 Templating Support: Create dynamic dashboards using Jinja2 templating
• 🔌 Extensible Architecture: Easy to extend and customize

Quick Start

Installation

pip install datadog-dashboard-deployer

Basic Usage

1. Set up your DataDog credentials:

export DATADOG_API_KEY='your-api-key'
export DATADOG_APP_KEY='your-application-key'

2. Create a dashboard configuration:

# config/dashboard_config.yaml
version: "1.0"
dashboards:
  - name: "System Overview"
    description: "System performance metrics"
    widgets:
      - title: "CPU Usage"
        type: "timeseries"
        query: "avg:system.cpu.user{*}"
      - title: "Memory Usage"
        type: "timeseries"
        query: "avg:system.mem.used{*}"

3. Deploy your dashboard:

datadog-dashboard-deploy config/dashboard_config.yaml

Project Structure

datadog-dashboard-deployer/
├── src/
│   └── datadog_dashboard_deployer/
│       ├── __init__.py
│       ├── core.py       # Core logic for dashboard creation
│       ├── config.py     # Configuration handling
│       └── utils.py      # Utility functions
├── config/
│   └── dashboard_config.yaml  # Main dashboard configuration
├── .github/
│   └── workflows/
│       └── deploy.yml      # GitHub Actions workflow
├── tests/                  # Test suite
├── docs/                   # Documentation
├── requirements.txt        # Project dependencies
├── setup.py               # Package configuration
└── README.md

Documentation

• Getting Started Guide
• Configuration Guide
• API Reference
• Examples

GitHub Actions Integration

1. Add DataDog credentials as secrets:

   • Go to repository Settings > Secrets and Variables > Actions
   • Add DATADOG_API_KEY and DATADOG_APP_KEY

2. Create a workflow file:

# .github/workflows/deploy.yml
name: Deploy Dashboards
on:
  push:
    branches: [main]
  workflow_dispatch:

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Set up Python
        uses: actions/setup-python@v2
        with:
          python-version: "3.x"
      - name: Deploy dashboards
        env:
          DATADOG_API_KEY: ${{ secrets.DATADOG_API_KEY }}
          DATADOG_APP_KEY: ${{ secrets.DATADOG_APP_KEY }}
        run: |
          pip install datadog-dashboard-deployer
          datadog-dashboard-deploy config/dashboard_config.yaml

Contributing

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

Development Setup

1. Clone the repository:

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

Security

• API keys are stored securely as environment variables or GitHub secrets
• Regular security audits and dependency updates
• See our Security Policy for details

Support

• GitHub Issues for bug reports and feature requests
• GitHub Discussions for questions and community support
• Stack Overflow using the datadog-dashboard-deployer tag

License

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

Acknowledgments

• DataDog for their excellent monitoring platform
• datadogpy for the official Python client
• All our contributors