Best Practices

Best Practices

Comprehensive guide to best practices when using the DataDog Dashboard Deployer.

Configuration Management

1. Version Control

• Store configurations in version control
• Use meaningful commit messages
• Follow branching strategy
• Review changes before deployment

2. File Organization

dashboards/
├── production/
│   ├── system-monitoring.yaml
│   └── application-metrics.yaml
├── staging/
│   ├── system-monitoring.yaml
│   └── application-metrics.yaml
└── templates/
    ├── widgets.yaml
    └── defaults.yaml

3. Naming Conventions

# Clear, descriptive names
dashboards:
  - name: "Production-WebAPI-Metrics"
    description: "Web API performance metrics for production"

# Consistent widget naming
widgets:
  - title: "[PROD] API Response Time"
    type: "timeseries"

Dashboard Design

1. Layout Organization

• Group related metrics
• Use consistent ordering
• Consider visual hierarchy
• Maintain readability

2. Widget Selection

# Choose appropriate widget types
widgets:
  # Use timeseries for trends
  - title: "CPU Trend"
    type: "timeseries"

  # Use query_value for current status
  - title: "Current Load"
    type: "query_value"

  # Use toplist for rankings
  - title: "Top Consumers"
    type: "toplist"

3. Query Optimization

# Efficient queries
queries:
  # Use appropriate aggregation
  good: "avg:system.cpu.user{*}.rollup(avg, 300)"
  bad: "avg:system.cpu.user{*}"

  # Limit cardinality
  good: "sum:requests{service:$service} by {endpoint}"
  bad: "sum:requests{*} by {host,endpoint,method,status}"

Security

1. Credential Management

• Use environment variables
• Rotate credentials regularly
• Implement least privilege
• Audit access regularly

2. Access Control

# Use appropriate tagging
defaults:
  tags:
    - "team:infrastructure"
    - "env:production"
    - "security-level:restricted"

CI/CD Integration

1. Workflow Setup

# .github/workflows/deploy.yml
name: Deploy Dashboards
on:
  push:
    branches: [main]
    paths:
      - "dashboards/**"

jobs:
  deploy:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Deploy
        env:
          DATADOG_API_KEY: ${{ secrets.DATADOG_API_KEY }}
          DATADOG_APP_KEY: ${{ secrets.DATADOG_APP_KEY }}
        run: |
          datadog-dashboard-deploy dashboards/production/*.yaml

2. Validation Steps

# Validate before deployment
datadog-dashboard-deploy --dry-run config.yaml

# Run tests
pytest tests/

# Check formatting
black . && isort .

Performance

1. Query Optimization

• Use appropriate time aggregation
• Limit high-cardinality tags
• Implement efficient filtering

2. Dashboard Efficiency

# Limit widgets per dashboard
dashboards:
  - name: "System Overview"
    widgets:
      # Keep widget count reasonable (8-12 max)
      - title: "CPU Usage"
        type: "timeseries"
      # ...

Monitoring and Maintenance

1. Regular Reviews

• Audit dashboard usage
• Update outdated metrics
• Remove unused dashboards
• Validate configurations

2. Documentation

dashboards:
  - name: "Service Monitoring"
    description: |
      Comprehensive service monitoring dashboard.
      Owner: Infrastructure Team
      Last Updated: 2024-02-06
      Contact: #infrastructure-support

Testing

1. Configuration Testing

def test_dashboard_config():
    """Test dashboard configuration validation."""
    config = load_config("dashboards/production/system.yaml")
    assert "version" in config
    assert len(config["dashboards"]) > 0

2. Deployment Testing

def test_dashboard_deployment():
    """Test dashboard deployment."""
    result = deployer.deploy("config.yaml", dry_run=True)
    assert result["status"] == "validated"

Related Resources

• Configuration Guide
• Templating Guide
• Security