Agent Skills
› rmyndharis/antigravity-skills
› grafana-dashboards
grafana-dashboards
GitHub用于创建和管理生产级 Grafana 仪表板，实现系统与应用指标的可观测性。支持 Prometheus 数据可视化、SLO 监控及业务 KPI 追踪，遵循 RED/USE 方法论与信息层级设计原则，提供 JSON 配置示例以构建高效监控界面。
触发场景
需要创建或修改 Grafana 监控仪表板
可视化 Prometheus 指标或系统性能数据
实施 SLO 监控或基础设施健康检查
追踪业务关键绩效指标 (KPI)
安装
npx skills add rmyndharis/antigravity-skills --skill grafana-dashboards -g -y
SKILL.md
Frontmatter
{
"name": "grafana-dashboards",
"description": "Create and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces."
}
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.
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
{
"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}
}
]
}
}
Panel Types
1. Stat Panel (Single Value)
{
"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
{
"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
{
"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
{
"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
{
"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_values(kube_service_info{namespace=\"$namespace\"}, service)",
"refresh": 1,
"multi": true
}
]
}
}
Use Variables in Queries
sum(rate(http_requests_total{namespace="$namespace", service=~"$service"}[5m]))
Alerts in Dashboards
{
"alert": {
"name": "High Error Rate",
"conditions": [
{
"evaluator": {
"params": [5],
"type": "gt"
},
"operator": {"type": "and"},
"query": {
"params": ["A", "5m", "now"]
},
"reducer": {"type": "avg"},
"type": "query"
}
],
"executionErrorState": "alerting",
"for": "5m",
"frequency": "1m",
"message": "Error rate is above 5%",
"noDataState": "no_data",
"notifications": [
{"uid": "slack-channel"}
]
}
}
Dashboard Provisioning
dashboards.yml:
apiVersion: 1
providers:
- name: 'default'
orgId: 1
folder: 'General'
type: file
disableDeletion: false
updateIntervalSeconds: 10
allowUiUpdates: true
options:
path: /etc/grafana/dashboards
Common Dashboard Patterns
Infrastructure Dashboard
Key Panels:
- CPU utilization per node
- Memory usage per node
- Disk I/O
- Network traffic
- Pod count by namespace
- Node status
Database Dashboard
Key Panels:
- Queries per second
- Connection pool usage
- Query latency (P50, P95, P99)
- Active connections
- Database size
- Replication lag
- Slow queries
Application Dashboard
Key Panels:
- Request rate
- Error rate
- Response time (percentiles)
- Active users/sessions
- Cache hit rate
- Queue length
Best Practices
- Start with templates (Grafana community dashboards)
- Use consistent naming for panels and variables
- Group related metrics in rows
- Set appropriate time ranges (default: Last 6 hours)
- Use variables for flexibility
- Add panel descriptions for context
- Configure units correctly
- Set meaningful thresholds for colors
- Use consistent colors across dashboards
- Test with different time ranges
Dashboard as Code
Terraform Provisioning
resource "grafana_dashboard" "api_monitoring" {
config_json = file("${path.module}/dashboards/api-monitoring.json")
folder = grafana_folder.monitoring.id
}
resource "grafana_folder" "monitoring" {
title = "Production Monitoring"
}
Ansible Provisioning
- name: Deploy Grafana dashboards
copy:
src: "{{ item }}"
dest: /etc/grafana/dashboards/
with_fileglob:
- "dashboards/*.json"
notify: restart grafana
Related Skills
prometheus-configuration- For metric collectionslo-implementation- For SLO dashboards
版本历史
- e63f7dd 当前 2026-07-05 09:33
