自定义监控大盘
在 KubeVela 中，借助 Kubernetes 原生的 Aggregated API Layer，KubeVela 用户可以比较轻易地在集群中操作修改 Grafana 上的监控大盘。
除了 开箱即用 章节中 grafana 插件预置的监控大盘外，KubeVela 用户同样也可以在系统中部署自定义大盘。
提示
如果你还不了解如何在 Grafana 上创建大盘并将它们以 JSON 格式导出，你可以阅读下列 Grafana 官方文档来学习。
使用应用组件部署监控大盘
一种部署监控大盘的方式是在 KubeVela 应用中使用相应的组件类型。
apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
name: my-dashboard
spec:
components:
- name: my-dashboard
type: grafana-dashboard
properties:
uid: my-example-dashboard
data: |
{
"panels": [{
"gridPos": {
"h": 9,
"w": 12
},
"targets": [{
"datasource": {
"type": "prometheus",
"uid": "prometheus-vela"
},
"expr": "max(up) by (cluster)"
}],
"title": "Clusters",
"type": "timeseries"
}],
"title": "My Dashboard"
}
使用应用运维特征部署监控大盘
除了组件外，用户也可以将监控大盘放在运维特征中进行部署。
apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
name: my-app
spec:
components:
- name: my-app
type: webservice
properties:
image: somefive/prometheus-client-example:new
traits:
- type: prometheus-scrape
- type: grafana-dashboard
properties:
data: |
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通过 URL 导入监控大盘
有时，你可能已经把编写好的 Grafana 监控大盘存储在了 OSS 或者其他 HTTP 服务器上。在 KubeVela 的应用中，你同样也可以使用 import-grafana-dashboard 工作流步骤来将大盘导入。
apiVersion: core.oam.dev/v1beta1
kind: Application
metadata:
name: my-dashboard
spec:
components: []
workflow:
steps:
- type: import-grafana-dashboard
name: import-grafana-dashboard
properties:
uid: my-dashboard
title: My Dashboard
url: https://kubevelacharts.oss-accelerate.aliyuncs.com/dashboards/up-cluster-dashboard.json
在 import-grafana-dashboard 步骤中, 应用首先将会从 URL 上下载监控大盘的数据，然后将它创建到 Grafana 上。
使用 CUE 来动态生成监控大盘
危险
下面的章节将会要求您具有一定的 CUE 语言开发经验，尤其是 KubeVela 的工作流自定义步骤的开发经验。此外，Grafana 监控大盘基础数据结构的相关知识也是必要的。如果缺少这些知识，下面的内容将会比较难理解。
下文是一个在 KubeVela 中实践 Dashboard as Code 的样例。当你在实际环境中使用它时，根据场景可能存在额外的问题需要注意，比如部分指标的延迟出现。目前该技术尚未使用在生产环境中，它是否能够在不同的环境中顺利运行也尚未验证。欢迎将你的想法和用例提交在 GitHub 上进行讨论。