Grafana Dashboard
Table of Contents
Overview
Design and implement comprehensive Grafana dashboards with multiple visualization types, variables, and drill-down capabilities for operational monitoring.
When to Use
- Creating monitoring dashboards
- Building operational insights
- Visualizing time-series data
- Creating drill-down dashboards
- Sharing metrics with stakeholders
Quick Start
Minimal working example:
{
"dashboard": {
"title": "Application Performance",
"description": "Real-time application metrics",
"tags": ["production", "performance"],
"timezone": "UTC",
"refresh": "30s",
"templating": {
"list": [
{
"name": "datasource",
"type": "datasource",
"datasource": "prometheus"
},
{
"name": "service",
"type": "query",
"datasource": "prometheus",
"query": "label_values(requests_total, service)"
}
]
},
"panels": [
{
"id": 1,
// ... (see reference guides for full implementation)
Reference Guides
Detailed implementations in the references/ directory:
| Guide | Contents | |---|---| | Grafana Dashboard JSON | Grafana Dashboard JSON | | Grafana Provisioning Configuration | Grafana Provisioning Configuration | | Grafana Alert Configuration | Grafana Alert Configuration | | Grafana API Client | Grafana API Client | | Docker Compose Setup | Docker Compose Setup |
Best Practices
✅ DO
- Use meaningful dashboard titles
- Add documentation panels
- Implement row-based organization
- Use variables for flexibility
- Set appropriate refresh intervals
- Include runbook links in alerts
- Test alerts before deploying
- Use consistent color schemes
- Version control dashboard JSON
❌ DON'T
- Overload dashboards with too many panels
- Mix different time ranges without justification
- Create without runbooks
- Ignore alert noise
- Use inconsistent metric naming
- Set refresh too frequently
- Forget to configure datasources
- Leave default passwords