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dashboarding

by @grafanav
4.4(120)

此技能专注于创建、修改和组织 Grafana 仪表盘,包括面板、变量和转换。它通过理解 JSON 结构,使用户能够以编程方式管理仪表盘,实现高效的数据可视化和监控,从而提升系统可观测性和决策效率。

grafanadashboardingdata-visualizationmonitoringobservabilityGitHub
安装方式
npx skills add https://github.com/grafana/skills --skill dashboarding
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Before / After 效果对比

1
使用前

用户或团队在没有此技能时,需要手动通过 Grafana UI 配置复杂的仪表盘,包括每个面板、变量和布局。这不仅耗时,而且容易出错,难以在不同环境或服务间保持一致性。

使用后

此技能通过理解仪表盘的 JSON 结构,使用户能够以编程方式创建和修改仪表盘。这大大减少了手动配置的时间,提高了仪表盘部署的效率和一致性,使监控设置变得快速且可重复。

SKILL.md

Grafana Dashboard Authoring

Dashboards are JSON documents stored in Grafana. Every dashboard has panels, variables, time range, and refresh settings. Understanding the JSON schema lets you programmatically create and modify dashboards via the API or Grafana Assistant tools.


Dashboard JSON structure

{
  "title": "My Dashboard",
  "uid": "my-dashboard-v1",
  "tags": ["service", "production"],
  "time": { "from": "now-1h", "to": "now" },
  "refresh": "30s",
  "timezone": "browser",
  "schemaVersion": 41,
  "templating": { "list": [] },
  "annotations": { "list": [] },
  "panels": []
}

Key fields:

  • uid - stable identifier used in URLs and API calls; keep it short and meaningful
  • schemaVersion - use 41 for Grafana 11+
  • time.from / to - supports relative (now-1h, now-7d) and absolute ISO timestamps
  • refresh - auto-refresh interval ("30s", "1m", "5m", "" for off)

Panel types and when to use them

PanelUse case
Time seriesAny metric over time; the default choice for counters, rates, gauges
StatSingle current value with optional sparkline (e.g. uptime, current RPS)
GaugePercent or value against a min/max (e.g. disk usage %)
Bar gaugeCompare multiple values side by side (e.g. top 10 services by RPS)
TableMulti-column data (e.g. alert list with labels)
HeatmapDistribution over time (e.g. request duration histogram)
LogsLoki log streams
TracesTempo trace search
TextMarkdown documentation panels
CandlestickOHLC/financial data (or min/max/avg patterns)
Node graphService dependency graphs

Panel JSON structure

{
  "id": 1,
  "type": "timeseries",
  "title": "Request Rate",
  "gridPos": { "x": 0, "y": 0, "w": 12, "h": 8 },
  "datasource": { "type": "prometheus", "uid": "${datasource}" },
  "targets": [
    {
      "expr": "sum(rate(http_requests_total{job=\"$job\"}[5m])) by (status_code)",
      "legendFormat": "{{status_code}}",
      "refId": "A"
    }
  ],
  "fieldConfig": {
    "defaults": {
      "unit": "reqps",
      "thresholds": {
        "mode": "absolute",
        "steps": [
          { "color": "green", "value": null },
          { "color": "yellow", "value": 1000 },
          { "color": "red", "value": 5000 }
        ]
      }
    },
    "overrides": []
  },
  "options": {
    "legend": { "calcs": ["mean", "max", "last"], "displayMode": "table", "placement": "bottom" },
    "tooltip": { "mode": "multi", "sort": "desc" }
  }
}

gridPos: The dashboard uses a 24-column grid. Common widths: full-width=24, half=12, third=8, quarter=6. Height in grid units (1 unit ≈ 30px).


Useful unit identifiers

# Rates
"reqps"      -- requests per second
"ops"        -- operations per second
"Bps"        -- bytes per second
"percentunit" -- 0.0-1.0 as percentage

# Storage
"bytes"      -- bytes (auto-scales to KB/MB/GB)
"decbytes"   -- decimal bytes (1 KB = 1000 B)

# Time
"ms"         -- milliseconds
"s"          -- seconds
"dtdurationms" -- duration in ms (shows as "1h 2m 3s")

# Counts
"short"      -- compact number (1.2k, 3.4M)
"none"       -- raw number

Full list: Panel > Field > Unit dropdown in Grafana UI, or the units reference.


Template variables

Variables make dashboards reusable across environments and services.

Query variable (populates from metric labels):

{
  "name": "job",
  "type": "query",
  "datasource": { "type": "prometheus", "uid": "prometheus" },
  "query": { "query": "label_values(up, job)", "refId": "A" },
  "refresh": 2,
  "includeAll": true,
  "multi": true,
  "label": "Service"
}

Constant variable:

{
  "name": "cluster",
  "type": "constant",
  "query": "production",
  "label": "Cluster"
}

Datasource variable (switch data sources without editing queries):

{
  "name": "datasource",
  "type": "datasource",
  "pluginId": "prometheus",
  "includeAll": false,
  "label": "Prometheus"
}

Use variables in queries:

# Reference a variable in a PromQL query
rate(http_requests_total{job=~"$job"}[5m])

# Multi-value variable uses regex OR automatically
# When $job = ["api", "worker"], it becomes job=~"api|worker"

Chain variables (second variable filters based on first):

{
  "name": "pod",
  "query": "label_values(kube_pod_info{namespace=\"$namespace\"}, pod)"
}

Transformations

Transformations run client-side after data is fetched, reshaping results without changing queries.

Common transformations:

"transformations": [
  {
    "id": "merge",
    "options": {}
  },
  {
    "id": "organize",
    "options": {
      "renameByName": { "Value #A": "Request Rate", "Value #B": "Error Rate" },
      "excludeByName": { "Time": true }
    }
  },
  {
    "id": "calculateField",
    "options": {
      "alias": "Error %",
      "mode": "reduceRow",
      "reduce": { "reducer": "last" },
      "binary": {
        "left": "errors",
        "right": "total",
        "operator": "/"
      }
    }
  },
  {
    "id": "filterByValue",
    "options": {
      "filters": [{ "fieldName": "Error %", "config": { "id": "greater", "options": { "value": 0.01 } } }],
      "type": "include",
      "match": "any"
    }
  }
]

Key transformation IDs: merge, organize, rename, calculateField, filterByValue, groupBy, sortBy, limit, labelsToFields, seriesToRows, partitionByValues.


Dashboard linking

Panel link (click a panel to go somewhere):

"links": [
  {
    "title": "Go to details",
    "url": "/d/details-dashboard?var-service=${__field.labels.service}",
    "targetBlank": false
  }
]

Dashboard link (top-right corner links):

"links": [
  {
    "title": "Runbook",
    "url": "https://wiki.example.com/runbook/${job}",
    "icon": "external link",
    "targetBlank": true,
    "type": "link"
  }
]

Built-in variables for links:

  • ${__value.raw} - current data point value
  • ${__field.labels.job} - label value from current series
  • ${__url.params} - current URL query parameters (pass-through)
  • ${__from} / ${__to} - current time range as Unix ms

Annotations

Show events overlaid on time series panels (deployments, incidents, etc.).

Query annotation from Loki:

{
  "datasource": { "type": "loki", "uid": "loki" },
  "expr": "{job=\"deployments\"} |= \"deployed\"",
  "name": "Deployments",
  "iconColor": "blue",
  "titleFormat": "{{service}} deployed",
  "textFormat": "{{version}} by {{author}}"
}

Query annotation from Prometheus:

{
  "datasource": { "type": "prometheus", "uid": "prometheus" },
  "expr": "changes(kube_deployment_status_observed_generation{namespace=\"production\"}[5m]) > 0",
  "step": "60s",
  "name": "Deployments",
  "iconColor": "blue",
  "titleFormat": "Deploy: {{deployment}}"
}

Dashboard via API

# Create or update a dashboard
curl -s -X POST \
  -H "Authorization: Bearer <API_KEY>" \
  -H "Content-Type: application/json" \
  "https://myorg.grafana.net/api/dashboards/db" \
  -d '{
    "dashboard": { <dashboard JSON> },
    "folderUid": "my-folder",
    "overwrite": true,
    "message": "Updated via API"
  }'

# Get a dashboard by UID
curl -s -H "Authorization: Bearer <API_KEY>" \
  "https://myorg.grafana.net/api/dashboards/uid/my-dashboard-v1" | jq '.dashboard'

# Search dashboards
curl -s -H "Authorization: Bearer <API_KEY>" \
  "https://myorg.grafana.net/api/search?query=kubernetes&type=dash-db" | \
  jq '.[] | {uid, title, folderTitle}'

# Create a folder
curl -s -X POST \
  -H "Authorization: Bearer <API_KEY>" \
  -H "Content-Type: application/json" \
  "https://myorg.grafana.net/api/folders" \
  -d '{"uid": "platform-team", "title": "Platform Team"}'

Grafana scenes (app plugins)

For dashboards embedded in app plugins, use @grafana/scenes instead of raw JSON. See the grafana-o11y:grafana-scenes skill for the React-based scenes API.


References

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安装量4.7K
评分4.4 / 5.0
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更新日期2026年9月15日
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创建2026年6月7日
最后更新2026年9月15日
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