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文档中心 > 容器服务 > 最佳实践 > 弹性伸缩 > 在 TKE 上使用自定义指标进行弹性伸缩

在 TKE 上使用自定义指标进行弹性伸缩

最近更新时间:2022-01-17 14:42:43

操作场景

容器服务 TKE 基于 Custom Metrics API 支持许多用于弹性伸缩的指标,涵盖 CPU、内存、硬盘、网络以及 GPU 相关的指标,覆盖绝大多数的 HPA 弹性伸缩场景,详细列表请参见 自动伸缩指标说明
针对例如基于业务单副本 QPS 大小来进行自动扩缩容等复杂场景,可通过安装 prometheus-adapter 来实现自动扩缩容。而 Kubernetes 提供 Custom Metrics APIExternal Metrics API 来对 HPA 指标进行扩展,让用户能够根据实际需求进行自定义。
prometheus-adapter 支持以上两种API,在实际环境中,使用 Custom Metrics API 即可满足大部分场景。本文将介绍如何通过 Custom Metrics API 实现使用自定义指标进行弹性伸缩。

前提条件

  • 已创建1.12或以上版本的 TKE 集群,详情请参见 创建集群
  • 已部署 Prometheus 并进行相应的自定义指标采集。
  • 已安装 Helm

操作步骤

暴露监控指标

本文以 Golang 业务程序为例,该示例程序暴露了 httpserver_requests_total 指标,并记录 HTTP 的请求,通过该指标可以计算出业务程序的 QPS 值。示例如下:

package main

import (
        "github.com/prometheus/client_golang/prometheus"
        "github.com/prometheus/client_golang/prometheus/promhttp"
        "net/http"
        "strconv"
)

var (
HTTPRequests = prometheus.NewCounterVec(
        prometheus.CounterOpts{
            Name: "httpserver_requests_total",
            Help: "Number of the http requests received since the server started",
        },
        []string{"status"},
    )
)

func init() {
    prometheus.MustRegister(HTTPRequests)
}

func main() {
    http.HandleFunc("/", func(w http.ResponseWriter, r *http.Request) {
        path := r.URL.Path
        code := 200
        switch path {
        case "/test":
            w.WriteHeader(200)
            w.Write([]byte("OK"))
        case "/metrics":
            promhttp.Handler().ServeHTTP(w, r)
        default:
            w.WriteHeader(404)
            w.Write([]byte("Not Found"))
        }
        HTTPRequests.WithLabelValues(strconv.Itoa(code)).Inc()
    })
    http.ListenAndServe(":80", nil)
}

部署业务程序

通过使用 Deployment 部署,将业务程序进行容器化并部署到 TKE 集群。示例如下:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: httpserver
  namespace: httpserver
spec:
  replicas: 1
  selector:
    matchLabels:
      app: httpserver
  template:
    metadata:
      labels:
        app: httpserver
    spec:
      containers:
      - name: httpserver
        image: imroc.tencentcloudcr.com/test/httpserver:v1
        imagePullPolicy: Always

---

apiVersion: v1
kind: Service
metadata:
  name: httpserver
  namespace: httpserver
  labels:
    app: httpserver
  annotations:
    prometheus.io/scrape: "true"
    prometheus.io/path: "/metrics"
    prometheus.io/port: "http"
spec:
  type: ClusterIP
  ports:
  - port: 80
    protocol: TCP
    name: http
  selector:
    app: httpserver

Prometheus 采集业务监控

您可以通过 Promtheus 采集规则ServiceMonitor 配置 Promtheus 采集业务暴露的监控指标。

方式1:配置 Promtheus 采集规则

在 Promtheus 的采集规则配置文件中添加以下采集规则。示例如下:

    - job_name: httpserver
        scrape_interval: 5s
        kubernetes_sd_configs:
        - role: endpoints
            namespaces:
                names:
                - httpserver
        relabel_configs:
        - action: keep
            source_labels:
            - __meta_kubernetes_service_label_app
            regex: httpserver
        - action: keep
            source_labels:
            - __meta_kubernetes_endpoint_port_name
            regex: http

方式2:配置 ServiceMonitor

若已安装 prometheus-operator,可以通过创建 ServiceMonitor 的 CRD 对象配置 Prometheus。示例如下:

apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: httpserver
spec:
  endpoints:
  - port: http
    interval: 5s
  namespaceSelector:
    matchNames:
    - httpserver
  selector:
    matchLabels:
      app: httpserver

安装 prometheus-adapter

  1. 使用 Helm 安装 prometheus-adapter,安装前请确定并配置自定义指标。按照上文 暴露监控指标 中的示例,在业务中使用 httpserver_requests_total 指标来记录 HTTP 请求,因此可以通过如下的 PromQL 计算出每个业务 Pod 的 QPS 监控。示例如下:
    sum(rate(http_requests_total[2m])) by (pod)
  2. 将其转换为 prometheus-adapter 的配置,创建 values.yaml,内容如下:
    rules:
          default: false
          custom:
          - seriesQuery: 'httpserver_requests_total'
            resources:
              template: <<.Resource>>
            name:
              matches: "httpserver_requests_total"
              as: "httpserver_requests_qps" # PromQL 计算出来的 QPS 指标
            metricsQuery: sum(rate(<<.Series>>{<<.LabelMatchers>>}[1m])) by (<<.GroupBy>>)
    prometheus:
          url: http://prometheus.monitoring.svc.cluster.local # 替换 Prometheus API 的地址 (不写端口)
          port: 9090
  3. 执行以下 Helm 命令安装 prometheus-adapter,示例如下:
    注意:

    安装前需要删除 TKE 已经注册的 Custom Metrics API,删除命令如下:
    kubectl delete apiservice v1beta1.custom.metrics.k8s.io

    helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
    helm repo update
    # Helm 3
    helm install prometheus-adapter prometheus-community/prometheus-adapter -f values.yaml
    # Helm 2
    # helm install --name prometheus-adapter prometheus-community/prometheus-adapter -f values.yaml

测试验证

若安装正确,执行以下命令,可以查看到 Custom Metrics API 返回配置的 QPS 相关指标。示例如下:

$ kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1
{
  "kind": "APIResourceList",
  "apiVersion": "v1",
  "groupVersion": "custom.metrics.k8s.io/v1beta1",
  "resources": [
    {
      "name": "jobs.batch/httpserver_requests_qps",
      "singularName": "",
      "namespaced": true,
      "kind": "MetricValueList",
      "verbs": [
        "get"
      ]
    },
    {
      "name": "pods/httpserver_requests_qps",
      "singularName": "",
      "namespaced": true,
      "kind": "MetricValueList",
      "verbs": [
        "get"
      ]
    },
    {
      "name": "namespaces/httpserver_requests_qps",
      "singularName": "",
      "namespaced": false,
      "kind": "MetricValueList",
      "verbs": [
        "get"
      ]
    }
  ]
}

执行以下命令,可以查看到 Pod 的 QPS 值。示例如下:

说明:

下述示例 QPS 为500m,表示 QPS 值为0.5。

$ kubectl get --raw /apis/custom.metrics.k8s.io/v1beta1/namespaces/httpserver/pods/*/httpserver_requests_qps
{
  "kind": "MetricValueList",
  "apiVersion": "custom.metrics.k8s.io/v1beta1",
  "metadata": {
    "selfLink": "/apis/custom.metrics.k8s.io/v1beta1/namespaces/httpserver/pods/%2A/httpserver_requests_qps"
  },
  "items": [
    {
      "describedObject": {
        "kind": "Pod",
        "namespace": "httpserver",
        "name": "httpserver-6f94475d45-7rln9",
        "apiVersion": "/v1"
      },
      "metricName": "httpserver_requests_qps",
      "timestamp": "2020-11-17T09:14:36Z",
      "value": "500m",
      "selector": null
    }
  ]
}

测试 HPA

假如设置每个业务 Pod 的平均 QPS 达到50时将触发扩容,最小副本为1个,最大副本为1000个,则配置示例如下:

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: httpserver
  namespace: httpserver
spec:
  minReplicas: 1
  maxReplicas: 1000
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: httpserver
  metrics:
  - type: Pods
    pods:
      metric:
        name: httpserver_requests_qps
      target:
        averageValue: 50
        type: AverageValue

执行以下命令对业务进行压测,观察是否自动扩容。示例如下:

$ kubectl get hpa
NAME         REFERENCE               TARGETS     MINPODS   MAXPODS   REPLICAS   AGE
httpserver   Deployment/httpserver   83933m/50   1         1000      2          18h
$ kubectl get pods
NAME                          READY   STATUS              RESTARTS   AGE
httpserver-6f94475d45-47d5w   1/1     Running             0          3m41s
httpserver-6f94475d45-7rln9   1/1     Running             0          37h
httpserver-6f94475d45-6c5xm   0/1     ContainerCreating   0          1s
httpserver-6f94475d45-wl78d   0/1     ContainerCreating   0          1s

若扩容正常,则说明已实现 HPA 基于业务自定义指标进行弹性伸缩。

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