共计 6117 个字符,预计需要花费 16 分钟才能阅读完成。
本文来自 Rancher Labs
在过来的文章中,咱们花了相当大的篇幅来聊对于监控的话题。这是因为当你正在治理 Kubernetes 集群时,所有都会以极快的速度发生变化。因而有一个工具来监控集群的衰弱状态和资源指标极为重要。
在 Rancher 2.5 中,咱们引入了基于 Prometheus Operator 的新版监控,它能够提供 Prometheus 以及相干监控组件的原生 Kubernetes 部署和治理。Prometheus Operator 能够让你监控集群节点、Kubernetes 组件和应用程序工作负载的状态和过程。同时,它还可能通过 Prometheus 收集的指标来定义告警并且创立自定义仪表盘,通过 Grafana 能够轻松地可视化收集到的指标。你能够拜访下列链接获取更多对于新版监控组件的细节:
https://rancher.com/docs/ranc…
新版本的监控也采纳 prometheus-adapter,开发人员能够利用其基于自定义指标和 HPA 扩大他们的工作负载。
在本文中,咱们将摸索如何利用 Prometheus Operator 来抓取自定义指标并利用这些指标进行高级工作负载治理。
装置 Prometheus
在 Rancher 2.5 中装置 Prometheus 极为简略。仅需拜访 Cluster Explorer -> Apps 并装置 rancher-monitoring 即可。
你须要理解以下默认设置:
prometheus-adapter
将会作为 chart 装置的一部分启用ServiceMonitorNamespaceSelector
留为空,容许 Prometheus 在所有命名空间中收集 ServiceMonitors
装置实现后,咱们能够从 Cluster Explorer 拜访监控组件。
部署工作负载
当初让咱们部署一个从应用层裸露自定义指标的示例工作负载。该工作负载裸露了一个简略的应用程序,该应用程序曾经应用 Prometheus client_golang 库进行了检测,并在 /metric
端点上提供了一些自定义指标。
它有两个指标:
- http_requests_total
- http_request_duration_seconds
以下 manifest 部署了工作负载、相干服务以及拜访该工作负载的 ingress:
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app.kubernetes.io/name: prometheus-example-app
name: prometheus-example-app
spec:
replicas: 1
selector:
matchLabels:
app.kubernetes.io/name: prometheus-example-app
template:
metadata:
labels:
app.kubernetes.io/name: prometheus-example-app
spec:
containers:
- name: prometheus-example-app
image: gmehta3/demo-app:metrics
ports:
- name: web
containerPort: 8080
---
apiVersion: v1
kind: Service
metadata:
name: prometheus-example-app
labels:
app.kubernetes.io/name: prometheus-example-app
spec:
selector:
app.kubernetes.io/name: prometheus-example-app
ports:
- protocol: TCP
port: 8080
targetPort: 8080
name: web
---
apiVersion: networking.k8s.io/v1beta1
kind: Ingress
metadata:
name: prometheus-example-app
spec:
rules:
- host: hpa.demo
http:
paths:
- path: /
backend:
serviceName: prometheus-example-app
servicePort: 8080
部署 ServiceMonitor
ServiceMonitor 是一个自定义资源定义(CRD),能够让咱们申明性地定义如何监控一组动静服务。
你能够拜访以下链接查看残缺的 ServiceMonitor 标准:
https://github.com/prometheus…
当初,咱们来部署 ServiceMonitor,Prometheus 用它来收集组成 prometheus-example-app Kubernetes 服务的 pod。
kind: ServiceMonitor
metadata:
name: prometheus-example-app
spec:
selector:
matchLabels:
app.kubernetes.io/name: prometheus-example-app
endpoints:
- port: web
如你所见,当初用户能够在 Rancher 监控中浏览 ServiceMonitor。
不久之后,新的 service monitor 和服务相关联的 pod 应该会反映在 Prometheus 服务发现中。
咱们也可能在 Prometheus 中看到指标。
部署 Grafana 仪表盘
在 Rancher 2.5 中,监控能够让用户将 Grafana 仪表盘存储为 cattle-dashboards
命名空间中的 ConfigMaps。
用户或集群管理员当初能够在这一命名空间中增加更多的仪表盘以扩大 Grafana 的自定义仪表盘。
Dashboard ConfigMap Example
apiVersion: v1
kind: ConfigMap
metadata:
name: prometheus-example-app-dashboard
namespace: cattle-dashboards
labels:
grafana_dashboard: "1"
data:
prometheus-example-app.json: |
{
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": "-- Grafana --",
"enable": true,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"type": "dashboard"
}
]
},
"editable": true,
"gnetId": null,
"graphTooltip": 0,
"links": [],
"panels": [
{"aliasColors": {},
"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": null,
"fieldConfig": {
"defaults": {"custom": {}
},
"overrides": []},
"fill": 1,
"fillGradient": 0,
"gridPos": {
"h": 9,
"w": 12,
"x": 0,
"y": 0
},
"hiddenSeries": false,
"id": 2,
"legend": {
"avg": false,
"current": false,
"max": false,
"min": false,
"show": true,
"total": false,
"values": false
},
"lines": true,
"linewidth": 1,
"nullPointMode": "null",
"percentage": false,
"pluginVersion": "7.1.5",
"pointradius": 2,
"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{"expr": "rate(http_requests_total{code=\"200\",service=\"prometheus-example-app\"}[5m])",
"instant": false,
"interval": "","legendFormat":"",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeRegions": [],
"timeShift": null,
"title": "http_requests_total_200",
"tooltip": {
"shared": true,
"sort": 0,
"value_type": "individual"
},
"type": "graph",
"xaxis": {
"buckets": null,
"mode": "time",
"name": null,
"show": true,
"values": []},
"yaxes": [
{
"format": "short",
"label": null,
"logBase": 1,
"max": null,
"min": null,
"show": true
},
{
"format": "short",
"label": null,
"logBase": 1,
"max": null,
"min": null,
"show": true
}
],
"yaxis": {
"align": false,
"alignLevel": null
}
},
{"aliasColors": {},
"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": null,
"description": "","fieldConfig": {"defaults": {"custom": {}
},
"overrides": []},
"fill": 1,
"fillGradient": 0,
"gridPos": {
"h": 8,
"w": 12,
"x": 0,
"y": 9
},
"hiddenSeries": false,
"id": 4,
"legend": {
"avg": false,
"current": false,
"max": false,
"min": false,
"show": true,
"total": false,
"values": false
},
"lines": true,
"linewidth": 1,
"nullPointMode": "null",
"percentage": false,
"pluginVersion": "7.1.5",
"pointradius": 2,
"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{"expr": "rate(http_requests_total{code!=\"200\",service=\"prometheus-example-app\"}[5m])",
"interval": "","legendFormat":"",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeRegions": [],
"timeShift": null,
"title": "http_requests_total_not_200",
"tooltip": {
"shared": true,
"sort": 0,
"value_type": "individual"
},
"type": "graph",
"xaxis": {
"buckets": null,
"mode": "time",
"name": null,
"show": true,
"values": []},
"yaxes": [
{
"format": "short",
"label": null,
"logBase": 1,
"max": null,
"min": null,
"show": true
},
{
"format": "short",
"label": null,
"logBase": 1,
"max": null,
"min": null,
"show": true
}
],
"yaxis": {
"align": false,
"alignLevel": null
}
}
],
"schemaVersion": 26,
"style": "dark",
"tags": [],
"templating": {"list": []
},
"time": {
"from": "now-15m",
"to": "now"
},
"timepicker": {
"refresh_intervals": [
"5s",
"10s",
"30s",
"1m",
"5m",
"15m",
"30m",
"1h",
"2h",
"1d"
]
},
"timezone": "","title":"prometheus example app","version": 1
}
当初,用户应该可能在 Grafana 中拜访 prometheus example app 的仪表盘。
自定义指标的 HPA
这一部分假如你曾经将 prometheus-adapter
作为监控的一部分装置结束了。实际上,在默认状况下,监控安装程序会装置 prometheus-adapter。
用户当初能够创立一个 HPA spec,如下所示:
apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
name: prometheus-example-app-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: prometheus-example-app
minReplicas: 1
maxReplicas: 5
metrics:
- type: Object
object:
describedObject:
kind: Service
name: prometheus-example-app
metric:
name: http_requests
target:
averageValue: "5"
type: AverageValue
你能够查看以下链接获取对于 HPA 的更多信息:
https://kubernetes.io/docs/ta…
咱们将应用自定义的 http_requests_total 指标来执行 pod 主动伸缩。
当初咱们能够生成一个样本负载来查看 HPA 的运行状况。我能够应用 hey
进行同样的操作。
hey -c 10 -n 5000 http://hpa.demo
总 结
在本文中,咱们探讨了 Rancher 2.5 中新监控的灵活性。开发人员和集群管理员能够利用该堆栈来监控它们的工作负载,部署可视化,并利用 Kubernetes 内可用的高级工作负载治理性能。