Create and manage production-ready Grafana dashboards for comprehensive system observability.
Scanned 9/11/2026
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---
name: grafana-dashboards
description: Create and manage production-ready Grafana dashboards for comprehensive system observability.
category: Creative & Media
source: antigravity
tags: [node, api, ai, template, design, cro]
url: https://github.com/sickn33/antigravity-awesome-skills/tree/main/skills/grafana-dashboards
---
# Grafana Dashboards
Create and manage production-ready Grafana dashboards for comprehensive system observability.
## Do not use this skill when
- The task is unrelated to grafana dashboards
- You need a different domain or tool outside this scope
## Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open `resources/implementation-playbook.md`.
## Purpose
Design effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.
## Use this skill when
- Visualize Prometheus metrics
- Create custom dashboards
- Implement SLO dashboards
- Monitor infrastructure
- Track business KPIs
## Dashboard Design Principles
### 1. Hierarchy of Information
```
┌─────────────────────────────────────┐
│ Critical Metrics (Big Numbers) │
├─────────────────────────────────────┤
│ Key Trends (Time Series) │
├─────────────────────────────────────┤
│ Detailed Metrics (Tables/Heatmaps) │
└─────────────────────────────────────┘
```
### 2. RED Method (Services)
- **Rate** - Requests per second
- **Errors** - Error rate
- **Duration** - Latency/response time
### 3. USE Method (Resources)
- **Utilization** - % time resource is busy
- **Saturation** - Queue length/wait time
- **Errors** - Error count
## Dashboard Structure
### API Monitoring Dashboard
```json
{
"dashboard": {
"title": "API Monitoring",
"tags": ["api", "production"],
"timezone": "browser",
"refresh": "30s",
"panels": [
{
"title": "Request Rate",
"type": "graph",
"targets": [
{
"expr": "sum(rate(http_requests_total[5m])) by (service)",
"legendFormat": "{{service}}"
}
],
"gridPos": {"x": 0, "y": 0, "w": 12, "h": 8}
},
{
"title": "Error Rate %",
"type": "graph",
"targets": [
{
"expr": "(sum(rate(http_requests_total{status=~\"5..\"}[5m])) / sum(rate(http_requests_total[5m]))) * 100",
"legendFormat": "Error Rate"
}
],
"alert": {
"conditions": [
{
"evaluator": {"params": [5], "type": "gt"},
"operator": {"type": "and"},
"query": {"params": ["A", "5m", "now"]},
"type": "query"
}
]
},
"gridPos": {"x": 12, "y": 0, "w": 12, "h": 8}
},
{
"title": "P95 Latency",
"type": "graph",
"targets": [
{
"expr": "histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))",
"legendFormat": "{{service}}"
}
],
"gridPos": {"x": 0, "y": 8, "w": 24, "h": 8}
}
]
}
}
```
**Reference:** See [inline example](#api-monitoring-dashboard)
## Panel Types
### 1. Stat Panel (Single Value)
```json
{
"type": "stat",
"title": "Total Requests",
"targets": [{
"expr": "sum(http_requests_total)"
}],
"options": {
"reduceOptions": {
"values": false,
"calcs": ["lastNotNull"]
},
"orientation": "auto",
"textMode": "auto",
"colorMode": "value"
},
"fieldConfig": {
"defaults": {
"thresholds": {
"mode": "absolute",
"steps": [
{"value": 0, "color": "green"},
{"value": 80, "color": "yellow"},
{"value": 90, "color": "red"}
]
}
}
}
}
```
### 2. Time Series Graph
```json
{
"type": "graph",
"title": "CPU Usage",
"targets": [{
"expr": "100 - (avg by (instance) (rate(node_cpu_seconds_total{mode=\"idle\"}[5m])) * 100)"
}],
"yaxes": [
{"format": "percent", "max": 100, "min": 0},
{"format": "short"}
]
}
```
### 3. Table Panel
```json
{
"type": "table",
"title": "Service Status",
"targets": [{
"expr": "up",
"format": "table",
"instant": true
}],
"transformations": [
{
"id": "organize",
"options": {
"excludeByName": {"Time": true},
"indexByName": {},
"renameByName": {
"instance": "Instance",
"job": "Service",
"Value": "Status"
}
}
}
]
}
```
### 4. Heatmap
```json
{
"type": "heatmap",
"title": "Latency Heatmap",
"targets": [{
"expr": "sum(rate(http_request_duration_seconds_bucket[5m])) by (le)",
"format": "heatmap"
}],
"dataFormat": "tsbuckets",
"yAxis": {
"format": "s"
}
}
```
## Variables
### Query Variables
```json
{
"templating": {
"list": [
{
"name": "namespace",
"type": "query",
"datasource": "Prometheus",
"query": "label_values(kube_pod_info, namespace)",
"refresh": 1,
"multi": false
},
{
"name": "service",
"type": "query",
"datasource": "Prometheus",
"query": "label_value
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