aj-geddes/grafana-dashboard

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