/grafana-dashboards

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.

Purpose

Design effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.

When to Use

• 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 }
      }
    ]
  }
}

**Reference:** See `assets/api-dashboard.json`

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
    allowUiUpda