【kubernetes/k8s概念】自定义metrics hpa使用

版权声明:本文为博主原创文章,未经博主允许不得转载。 https://blog.csdn.net/zhonglinzhang/article/details/86236925

kubernetes v1.12.1

从 v1.8 开始,资源使用情况的度量(如容器的 CPU 和内存使用)可以通过 Metrics API 获取。注意

Metrics API 只可以查询当前的度量数据,并不保存历史数据

Metrics API URI 为 /apis/metrics.k8s.io/,在 k8s.io/metrics 维护

必须部署 metrics-server 才能使用该 API,metrics-server 通过调用 Kubelet Summary API 获取数据

Kubernetes 监控架构

Kubernetes 监控架构由以下两部分组成:

  • 核心度量流程(下图黑色部分):这是 Kubernetes 正常工作所需要的核心度量,从 Kubelet、cAdvisor 等获取度量数据,再由 metrics-server 提供给 Dashboard、HPA 控制器等使用。

  • 监控流程(下图蓝色部分):基于核心度量构建的监控流程,比如 Prometheus 可以从 metrics-server 获取核心度量,从其他数据源(如 Node Exporter 等)获取非核心度量,再基于它们构建监控告警系统。

引用:https://kubernetes.feisky.xyz/bu-shu-pei-zhi/index-1/metrics#bu-shu-metricsserver

证书文件

    需要使用TLS证书对通信进行加密,这里我们使用CloudFlare的PKI 工具集cfssl 来生成Certificate Authority(CA) 证书和密钥文件, CA 是自签名的证书,用来签名后续创建的其他TLS 证书,

   安装 CFSSL

$ wget https://pkg.cfssl.org/R1.2/cfssl_linux-amd64

$ chmod +x cfssl_linux-amd64

$ sudo mv cfssl_linux-amd64 /usr/k8s/bin/cfssl

$ wget https://pkg.cfssl.org/R1.2/cfssljson_linux-amd64

$ chmod +x cfssljson_linux-amd64

$ sudo mv cfssljson_linux-amd64 /usr/k8s/bin/cfssljson

$ wget https://pkg.cfssl.org/R1.2/cfssl-certinfo_linux-amd64

$ chmod +x cfssl-certinfo_linux-amd64

$ sudo mv cfssl-certinfo_linux-amd64 /usr/k8s/bin/cfssl-certinfo

    主要用在Metrics API aggregator 上

# cat metrics-ca-csr.json 
{
    "CN": "kubernetes",
    "key": {
        "algo": "rsa",
        "size": 2048
    }
}

# cat metrics-client-csr.json 
{
    "CN": "metrics-client",
    "key": {
        "algo": "rsa",
        "size": 2048
    }
}

   生成CA 证书和私钥

# cfssl gencert -initca metrics-ca-csr.json | cfssljson -bare metrics-ca

# cfssl gencert -ca=metrics-ca.pem -ca-key=metrics-ca-key.pem -config=/etc/kubernetes/ssl/ca-config.json -profile=kubernetes metrics-client-csr.json | cfssljson -bare metrics-client

    将证书传到所有运行kube-apiserver的节点

    scp metrics* [email protected]:/etc/kubernetes/ssl/

kube-apiserver启动配置

  •  --requestheader-client-ca-file: 根证书绑定包用于在信任--requestheader-username-headers指定的标头中的用户名前,在传入请求上验证客户证书
  •  --requestheader-allowed-names:  客户端证书常用名称列表,允许在--requestheader-username-headers指定的标头中提供用户名,如果为空,则允许在--requestheader-client-ca文件中通过当局验证的任何客户端证书
  •  --requestheader-extra-headers-prefix:  要检查的请求标头前缀列表
  •  --requestheader-group-headers:  要检查组的请求标头列表
  • --requestheader-username-headers:  要检查用户名的请求标头列表
  • --proxy-client-cert-file:  用于证明aggregator或kube-apiserver在请求期间发出呼叫的身份的客户端证书
  • --proxy-client-key-file:  用于证明聚合器或kube-apiserver的身份的客户端证书的私钥,当它必须在请求期间调用时使用。包括将请求代理给用户api-server和调用webhook admission插件
  • --enable-aggregator-routing=true:  打开aggregator路由请求到endpoints IP,而不是集群IP

cat /etc/systemd/system/kube-apiserver.service

[Service]
ExecStart=/usr/bin/kube-apiserver \
  --admission-control=NamespaceLifecycle,LimitRanger,ServiceAccount,DefaultStorageClass,ResourceQuota \
  --advertise-address=10.12.51.171 \
  --bind-address=0.0.0.0 \
  --insecure-bind-address=127.0.0.1 \
  --authorization-mode=Node,RBAC \
  --kubelet-https=true \
  --token-auth-file=/etc/kubernetes/token.csv \
  --service-cluster-ip-range=10.254.0.0/16 \
  --service-node-port-range=30000-52766 \
  --tls-cert-file=/etc/kubernetes/ssl/kubernetes.pem \
  --tls-private-key-file=/etc/kubernetes/ssl/kubernetes-key.pem \
  --client-ca-file=/etc/kubernetes/ssl/ca.pem \
  --service-account-key-file=/etc/kubernetes/ssl/ca-key.pem \
  --etcd-cafile=/etc/kubernetes/ssl/ca.pem \
  --etcd-certfile=/etc/kubernetes/ssl/kubernetes.pem \
  --etcd-keyfile=/etc/kubernetes/ssl/kubernetes-key.pem \
  --etcd-servers=https://10.12.51.171:2379,https://10.12.51.172:2379 \
  --enable-swagger-ui=true \
  --allow-privileged=true \
  --apiserver-count=2 \
  --audit-log-maxage=30 \
  --audit-log-maxbackup=3 \
  --audit-log-maxsize=100 \
  --audit-log-path=/var/lib/audit.log \
  --event-ttl=1h \
  --logtostderr=true \
  --requestheader-client-ca-file=/etc/kubernetes/ssl/metrics-ca.pem \
  --requestheader-allowed-names=aggregator \
  --requestheader-extra-headers-prefix=X-Remote-Extra- \
  --requestheader-group-headers=X-Remote-Group \
  --requestheader-username-headers=X-Remote-User \
  --proxy-client-cert-file=/etc/kubernetes/ssl/metrics-client.pem \
  --proxy-client-key-file=/etc/kubernetes/ssl/metrics-client-key.pem \
  --enable-aggregator-routing=true \
  --v=4

kube-controller-manager启动配置

  kubernetes 1.12.1 已经启动设置 --horizontal-pod-autoscaler-use-rest-clients="true"

  初始化client代码为: sttartHPAControllerWIthRESTClient

  这个无须设置

github: https://github.com/stefanprodan/k8s-prom-hpa

部署prometheus

   kubectl apply -f prometheus  

   或者使用自己的方式部署

  • kube-state-metrics: 收集k8s集群内资源对象数据
  • node_exporter: 收集集群中各节点的数据
  • prometheus: 收集apiserver,scheduler,controller-manager,kubelet组件数据
  • alertmanager: 实现监控报警
  • grafana: 实现数据可视化

1. metrics-server方式

     metric-server收集数据给k8s集群内使用,如kubectl,hpa,scheduler等

   1.1 修改文件metrics-server/metrics-server-deployment.yaml

     否则出现错误: 

error: You must be logged in to the server (Unauthorized)
    spec:
      serviceAccountName: metrics-server
      volumes:
      # mount in tmp so we can safely use from-scratch images and/or read-only containers
      - name: tmp-dir
        hostPath:
          path: /etc/kubernetes/ssl
      containers:
      - command:
        - /metrics-server
        - --kubelet-insecure-tls
        #- --source=kubernetes.summary_api:https://kubernetes.default.svc?kubeletHttps=true&kubeletPort=10250&useServiceAccount=true&insecure=true
        - --requestheader-client-ca-file=/etc/kubernetes/ssl/metrics-ca.pem
        name: metrics-server
        image: zhangzhonglin/metrics-server-amd64:v0.3.1
        imagePullPolicy: Always
        volumeMounts:
        - name: tmp-dir
          mountPath: /etc/kubernetes/ssl

  1.2 并部署kubectl apply -f metrics-server

  1.3 测试1  

     kubectl get apiservice v1beta1.metrics.k8s.io -o yaml

apiVersion: apiregistration.k8s.io/v1
kind: APIService
metadata:
  annotations:
    kubectl.kubernetes.io/last-applied-configuration: |
      {"apiVersion":"apiregistration.k8s.io/v1beta1","kind":"APIService","metadata":{"annotations":{},"name":"v1beta1.metrics.k8s.io"},"spec":{"group":"metrics.k8s.io","groupPriorityMinimum":100,"insecureSkipTLSVerify":true,"service":{"name":"metrics-server","namespace":"kube-system"},"version":"v1beta1","versionPriority":100}}
  creationTimestamp: 2019-01-10T08:36:10Z
  name: v1beta1.metrics.k8s.io
  resourceVersion: "9491888"
  selfLink: /apis/apiregistration.k8s.io/v1/apiservices/v1beta1.metrics.k8s.io
  uid: c81ed0de-14b2-11e9-a6a8-00505683f77b
spec:
  group: metrics.k8s.io
  groupPriorityMinimum: 100
  insecureSkipTLSVerify: true
  service:
    name: metrics-server
    namespace: kube-system
  version: v1beta1
  versionPriority: 100
status:
  conditions:
  - lastTransitionTime: 2019-01-11T03:32:59Z
    message: all checks passed
    reason: Passed
    status: "True"
    type: Available

  1.4 测试2  

    kubectl get --raw "/apis/metrics.k8s.io/v1beta1/nodes" | jq .

  1.5 测试3

    kubectl get --raw "/apis/metrics.k8s.io/v1beta1/pods" | jq .

{
  "kind": "PodMetricsList",
  "apiVersion": "metrics.k8s.io/v1beta1",
  "metadata": {
    "selfLink": "/apis/metrics.k8s.io/v1beta1/pods"
  },
  "items": [
    {
      "metadata": {
        "name": "podinfo-c7cb8dfdd-dq48b",
        "namespace": "default",
        "selfLink": "/apis/metrics.k8s.io/v1beta1/namespaces/default/pods/podinfo-c7cb8dfdd-dq48b",
        "creationTimestamp": "2019-01-11T03:51:26Z"
      },
      "timestamp": "2019-01-11T03:52:49Z",
      "window": "30s",
      "containers": [
        {
          "name": "podinfod",
          "usage": {
            "cpu": "1357770n",
            "memory": "12396Ki"
          }
        }
      ]
    },

测试

   部署一个应用,主要是设置request,hpa根据这个处理,基于cpu metrics

   创建hpa,kubectl autoscale deploy bbbbbbbbbbb --min=1 --max=10 --cpu-percent=80

   在pod容器中加入stress压测工具执行 ./stress -c 1

    查看cpu情况

    查看hpa处理pod情况,已经扩容了好几个pod

  将stress进程kill掉,发现一会hpa controller缩容到1个副本

参考:

  https://kubernetes.feisky.xyz/bu-shu-pei-zhi/index-1/metrics#bu-shu-metricsserver

  https://github.com/kubernetes-incubator/custom-metrics-apiserver

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转载自blog.csdn.net/zhonglinzhang/article/details/86236925