---name: grafana-dashboarddescription: >---

Grafana Dashboard

Table of Contents

• Overview
• When to Use
• Quick Start
• Reference Guides
• Best Practices

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