Agent skill

grafana-dashboards

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.

View SKILL.md on GitHub Repository
Stars 152
Forks 20

Install this agent skill to your Project

npx add-skill https://github.com/Microck/ordinary-claude-skills/tree/main/skills_categorized/cicd/grafana-dashboards

SKILL.md

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

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 assets/api-dashboard.json

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_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

json
{
  "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:

yaml
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

Reference: See assets/infrastructure-dashboard.json

Database Dashboard

Key Panels:

  • Queries per second
  • Connection pool usage
  • Query latency (P50, P95, P99)
  • Active connections
  • Database size
  • Replication lag
  • Slow queries

Reference: See assets/database-dashboard.json

Application Dashboard

Key Panels:

  • Request rate
  • Error rate
  • Response time (percentiles)
  • Active users/sessions
  • Cache hit rate
  • Queue length

Best Practices

  1. Start with templates (Grafana community dashboards)
  2. Use consistent naming for panels and variables
  3. Group related metrics in rows
  4. Set appropriate time ranges (default: Last 6 hours)
  5. Use variables for flexibility
  6. Add panel descriptions for context
  7. Configure units correctly
  8. Set meaningful thresholds for colors
  9. Use consistent colors across dashboards
  10. Test with different time ranges

Dashboard as Code

Terraform Provisioning

hcl
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

yaml
- name: Deploy Grafana dashboards
  copy:
    src: "{{ item }}"
    dest: /etc/grafana/dashboards/
  with_fileglob:
    - "dashboards/*.json"
  notify: restart grafana

Reference Files

  • assets/api-dashboard.json - API monitoring dashboard
  • assets/infrastructure-dashboard.json - Infrastructure dashboard
  • assets/database-dashboard.json - Database monitoring dashboard
  • references/dashboard-design.md - Dashboard design guide

Related Skills

  • prometheus-configuration - For metric collection
  • slo-implementation - For SLO dashboards

Recommended Agent Skills

Expand your agent's capabilities with these related and highly-rated skills.

Microck/ordinary-claude-skills

nondominium-holochain-dna-dev

Specialized skill for nondominium Holochain DNA development, focusing on zome creation, entry patterns, integrity/coordinator architecture, ValueFlows compliance, and WASM optimization. Use when creating new zomes, implementing entry types, or modifying Holochain DNA code.

152 20
Explore
Microck/ordinary-claude-skills

fluidsim

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.

152 20
Explore
Microck/ordinary-claude-skills

metabolomics-workbench-database

Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.

152 20
Explore
Microck/ordinary-claude-skills

run-tests

Validate code changes by intelligently selecting and running the appropriate test suites. Use this when editing code to verify changes work correctly, run tests, validate functionality, or check for regressions. Automatically discovers affected test suites, selects the minimal set of venvs needed for validation, and handles test execution with Docker services as needed.

152 20
Explore
Microck/ordinary-claude-skills

skill-navigator

The 100th skill! Your intelligent guide to all 99 other skills. Recommends the perfect skill for any task, creates skill combinations, and helps you discover capabilities you didn't know you had.

152 20
Explore
Microck/ordinary-claude-skills

AgentDB Advanced Features

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

152 20
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results