关于 grafana-dashboards
面向 Grafana 仪表板设计与维护人员,提供应用、基础设施和业务指标可视化的设计模式与配置示例。内容包括面板、变量、告警及通过 Terraform 或 Ansible 配置仪表板。
主要功能
- 01API、基础设施及数据库仪表板模式
- 02统计图、时序图、表格与热图
- 03查询变量与动态筛选
- 04仪表板告警配置
- 05Terraform 和 Ansible 配置
适用场景
- 01展示 Prometheus 指标
- 02构建 SLO 仪表板
- 03监控基础设施与服务
- 04跟踪业务 KPI
安装
复制下面的命令,在终端中运行。
$
npx skills add https:/ / github.com/ hermeticormus/ libreuiux-claude-code --skill grafana-dashboards安装后在 Claude Code 中输入/grafana-dashboards确认已加载。
详细介绍
Grafana 仪表板
创建并管理可用于生产环境的 Grafana 仪表板,实现全面的系统可观测性。
用途
设计有效的 Grafana 仪表板,用于监控应用程序、基础设施和业务指标。
适用场景
- 可视化 Prometheus 指标
- 创建自定义仪表板
- 实现 SLO 仪表板
- 监控基础设施
- 跟踪业务 KPI
仪表板设计原则
1. 信息层级
┌─────────────────────────────────────┐
│ Critical Metrics (Big Numbers) │
├─────────────────────────────────────┤
│ Key Trends (Time Series) │
├─────────────────────────────────────┤
│ Detailed Metrics (Tables/Heatmaps) │
└─────────────────────────────────────┘
2. RED 方法(服务)
- 速率 - 每秒请求数
- 错误 - 错误率
- 耗时 - 延迟/响应时间
3. USE 方法(资源)
- 利用率 - 资源繁忙的时间百分比
- 饱和度 - 队列长度/等待时间
- 错误 - 错误计数
仪表板结构
API 监控仪表板
{
"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}
}
]
}
}
参考: 请参阅 assets/api-dashboard.json
面板类型
1. 统计面板(单值)
{
"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. 时间序列图
{
"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. 表格面板
{
"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. 热力图
{
"type": "heatmap",
"title": "Latency Heatmap",
"targets": [{
"expr": "sum(rate(http_request_duration_seconds_bucket[5m])) by (le)",
"format": "heatmap"
}],
"dataFormat": "tsbuckets",
"yAxis": {
"format": "s"
}
}
变量
查询变量
{
"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=\"$namespace\"}, service)",
"refresh": 1,
"multi": true
}
]
}
}
在查询中使用变量
sum(rate(http_requests_total{namespace="$namespace", service=~"$service"}[5m]))
仪表板中的告警
{
"alert": {
"name": "High Error Rate",
"conditions": [
{
"evaluator": {
"params": [5],
"type": "gt"
},
"operator": {"type": "and"},
"query": {
"params": ["A", "5m", "now"]
},
"reducer": {"type": "avg"},
"type": "query"
}
],
"executionErrorState": "alerting",
"for": "5m",
"frequency": "1m",
"message": "Error rate is above 5%",
"noDataState": "no_data",
"notifications": [
{"uid": "slack-channel"}
]
}
}
仪表板配置
dashboards.yml:
apiVersion: 1
providers:
- name: 'default'
orgId: 1
folder: 'General'
type: file
disableDeletion: false
updateIntervalSeconds: 10
allowUiUpdates: true
options:
path: /etc/grafana/dashboards
常见仪表板模式
基础设施仪表板
关键面板:
- 每个节点的 CPU 利用率
- 每个节点的内存使用量
- 磁盘 I/O
- 网络流量
- 各命名空间的 Pod 数量
- 节点状态
参考: 请参阅 assets/infrastructure-dashboard.json
数据库仪表板
关键面板:
- 每秒查询数
- 连接池使用情况
- 查询延迟(P50、P95、P99)
- 活跃连接数
- 数据库大小
- 复制延迟
- 慢查询
参考: 请参阅 assets/database-dashboard.json
应用程序仪表板
关键面板:
- 请求速率
- 错误率
- 响应时间(百分位数)
- 活跃用户/会话
- 缓存命中率
- 队列长度
最佳实践
- 从模板开始(Grafana 社区仪表板)
- 为面板和变量使用一致的命名
- 将相关指标分组到行中
- 设置合适的时间范围(默认:最近 6 小时)
- 使用变量以提高灵活性
- 添加面板说明以提供上下文
- 正确配置单位
- 设置有意义的颜色阈值
- 在各仪表板中使用一致的颜色
- 使用不同的时间范围进行测试
仪表板即代码
Terraform 配置
resource "grafana_dashboard" "api_monitoring" {
config_json = file("${path.module}/dashboards/api-monitoring.json")
folder = grafana_folder.monitoring.id
}
resource "grafana_folder" "monitoring" {
title = "Production Monitoring"
}
Ansible 配置
- name: Deploy Grafana dashboards
copy:
src: "{{ item }}"
dest: /etc/grafana/dashboards/
with_fileglob:
- "dashboards/*.json"
notify: restart grafana
参考文件
assets/api-dashboard.json- API 监控仪表板assets/infrastructure-dashboard.json- 基础设施仪表板assets/database-dashboard.json- 数据库监控仪表板references/dashboard-design.md- 仪表板设计指南
相关技能
prometheus-configuration- 用于指标采集slo-implementation- 用于 SLO 仪表板
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