Kubernetes -- Horizontal Pod Autoscaler

时间 2019-11-12 标签 kubernetes horizontal pod autoscaler

前言

在kubernetes中，咱们使用pod对外提供服务。这时候，咱们须要如下两种情形须要关注：php

pod由于不明缘由挂掉，致使服务不可用css
Pod在高负荷的状况下，不能支撑咱们的服务node

若是咱们人工监控pods，人工进行调整副本那么这个工做量无疑是巨大的，但kubernetes已经有了相应的机制来应对了。docker

那么今天就来介绍一下在k8s 1.6中的弹性伸缩的实施shell

k8s是kubernetes的官方简称
HPA全称Horizontal Pod Autoscaler数据库

HPA的原理

Kubernetes有一个HPA(Horizontal Pod Autoscaler)的资源，能够实现基于CPU使用率的Pod自动伸缩的功能。HPA基于Master Node上的kube-controller-manager服务启动参数–horizontal-pod-autoscaler-sync-period定义的时长(默认为30秒)，周期性的检测Pod的CPU使用率(须要事先安装heapster)。若是须要设置–horizontal-pod-autoscaler-sync-period能够在Master Node上的/etc/default/kube-controller-manager中修改。vim

安装Heapster

K8S从1.8版本开始，CPU、内存等资源的metrics信息能够经过 Metrics API来获取，用户能够直接获取这些metrics信息（例如经过执行kubect top命令），HPA使用这些metics信息来实现动态伸缩，可是在以前咱们使用Heapster来收集节点的相关数据api

导入相关镜像

咱们在实施的时候通常会建立/data目录，把全部的deployment放在此目录下，所以在k8s master建立kube-system目录ruby

[root@master data]# mkdir kube-system

上传相镜像，并导入

# 导入heasper [root@master kube-system]# docker load < heapster_3.tar 38ac8d0f5bb3: Loading layer [==================================================>] 1.312MB/1.312MB 388f58c4d5b0: Loading layer [==================================================>] 99.87MB/99.87MB c6772246bc46: Loading layer [==================================================>] 281.1kB/281.1kB Loaded image: registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1:v1.3.0-beta.1 # 导入influxdb数据库 [root@master kube-system]# docker load < influxdb13.tar 7da815924651: Loading layer [==================================================>] 10.48MB/10.48MB 2d447b9e914f: Loading layer [==================================================>] 5.12kB/5.12kB Loaded image: registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64:latest

查看导入imagesapp

[root@master kube-system]# docker images |grep heapster registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1 v1.3.0-beta.1 6393b81e2220 17 months ago 101MB registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64 latest d3fccbedd180 22 months ago 11.6MB

修改images tag以便咱们能够导入到私有registry中

[root@master kube-system]# docker tag registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1:v1.3.0-beta.1 registry.k8s.osc:5000/heapster:v1.3.0 [root@master kube-system]# docker tag registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64 registry.k8s.osc:5000/heapster-influxdb # 查看修改后的images [root@master kube-system]# docker images |grep heapster registry.cn-hangzhou.aliyuncs.com/lczean/heapster-amd64-v1.3.0-beta.1 v1.3.0-beta.1 6393b81e2220 17 months ago 101MB registry.k8s.osc:5000/heapster v1.3.0 6393b81e2220 17 months ago 101MB registry.cn-hangzhou.aliyuncs.com/golden/heapster-influxdb-amd64 latest d3fccbedd180 22 months ago 11.6MB registry.k8s.osc:5000/heapster-influxdb latest d3fccbedd180 22 months ago 11.6MB

推送到私有仓库

[root@master kube-system]# docker push registry.k8s.osc:5000/heapster:v1.3.0
The push refers to repository [registry.k8s.osc:5000/heapster]
c6772246bc46: Pushed 
388f58c4d5b0: Pushed 
38ac8d0f5bb3: Pushed 
v1.3.0: digest: sha256:e23b30d2e131e042eec9b5fdc30af905b63e454d140dc335246e74a4e8b4c857 size: 949
[root@master kube-system]# docker push registry.k8s.osc:5000/heapster-influxdb 
The push refers to repository [registry.k8s.osc:5000/heapster-influxdb]
2d447b9e914f: Pushed 
7da815924651: Pushed 
38ac8d0f5bb3: Mounted from heapster 
latest: digest: sha256:d2ecd285eb6585d56e8853da7b9fd8f4a57de4a3006f6720173a3f3942c0e7c9 size: 945

influxdb时间序列库介绍

建立deployment

[root@master kube-system]# vim influxdb-deployment.yaml
[root@master kube-system]# vim influxdb-service.yaml
[root@master kube-system]# vim heapster-deployment.yaml
[root@master kube-system]# vim heapster-service.yaml

分别看一下yaml：
influxdb-deployment.yaml
修改image

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: monitoring-influxdb
  namespace: kube-system
spec:
  replicas: 1
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: influxdb
    spec:
      volumes:
      - name: influxdb-storage
        emptyDir: {}
      containers:
      - name: influxdb
        image: registry.k8s.osc:5000/heapster-influxdb
        volumeMounts:
        - mountPath: /data
          name: influxdb-storage

influxdb-service.yaml

apiVersion: v1
kind: Service
metadata:
  labels:
    task: monitoring
    kubernetes.io/cluster-service: 'true'
    kubernetes.io/name: monitoring-influxdb
  name: monitoring-influxdb
  namespace: kube-system
spec:
  ports:
  - name: http
    port: 8083
    targetPort: 8083
  - name: api
    port: 8086
    targetPort: 8086
  selector:
    k8s-app: influxdb

建立deployment、service

[root@master kube-system]# kubectl create -f influxdb-deployment.yaml 
[root@master kube-system]# kubectl create -f influxdb-service.yaml

安装这两个后查看influxdb坐在的pod ip

[root@master kube-system]# kubectl get pods -n kube-system -o wide NAME READY STATUS RESTARTS AGE IP NODE monitoring-influxdb-3696415694-q9tds 1/1 Running 0 16m 172.99.39.6 172.16.187.158

测试安装正常，再安装flanneld的node访问如下连接，若是无报错说明安装成功

[root@node0 ~]# curl http://172.99.39.6:8086/ping

建立heapster-deployment.yaml
修改image、--source、--sink

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: heapster
  namespace: kube-system
spec:
  replicas: 1
  template:
    metadata:
      labels:
        task: monitoring
        k8s-app: heapster
        version: v6
    spec:
      containers:
      - name: heapster
        image: registry.k8s.osc:5000/heapster:v1.3.0
        imagePullPolicy: Always
        command:
        - /heapster
        - --source=kubernetes:http://172.16.187.162:8080
        - --sink=influxdb:http://172.99.39.6:8086

建立heapster-service.yaml

apiVersion: v1
kind: Service
metadata:
  labels:
    task: monitoring  
    kubernetes.io/cluster-service: 'true'
    kubernetes.io/name: Heapster
  name: heapster
  namespace: kube-system
spec:
  ports:
  - port: 80
    targetPort: 8082
  selector:
    k8s-app: heapster

建立heapster的deployment、service

[root@master kube-system]# kubectl create -f heapster-deployment.yaml 
deployment "heapster" created
[root@master kube-system]# kubectl create -f heapster-service.yaml 
service "heapster" created

所有安装后能够查看日志是不是正常启动的

[root@master kube-system]# kubectl get pods -n kube-system -o wide NAME READY STATUS RESTARTS AGE IP NODE heapster-1258036176-sjg7s 1/1 Running 0 1m 172.99.93.13 172.16.187.160 monitoring-influxdb-3696415694-q9tds 1/1 Running 0 26m 172.99.39.6 172.16.187.158 [root@master kube-system]# kubectl logs -f monitoring-influxdb-3696415694-q9tds -n kube-system 8888888 .d888 888 8888888b. 888888b. 888 d88P" 888 888 "Y88b 888 "88b 888 888 888 888 888 888 .88P 888 88888b. 888888 888 888 888 888 888 888 888 8888888K. 888 888 "88b 888 888 888 888 Y8bd8P' 888 888 888 "Y88b 888 888 888 888 888 888 888 X88K 888 888 888 888 888 888 888 888 888 Y88b 888 .d8""8b. 888 .d88P 888 d88P 8888888 888 888 888 888 "Y88888 888 888 8888888P" 8888888P" [run] 2018/12/07 05:27:33 InfluxDB starting, version unknown, branch unknown, commit unknown [run] 2018/12/07 05:27:33 Go version go1.7.4, GOMAXPROCS set to 16 [run] 2018/12/07 05:27:33 Using configuration at: /etc/config.toml [store] 2018/12/07 05:27:33 Using data dir: /data/data [subscriber] 2018/12/07 05:27:33 opened service [monitor] 2018/12/07 05:27:33 Starting monitor system [monitor] 2018/12/07 05:27:33 'build' registered for diagnostics monitoring [monitor] 2018/12/07 05:27:33 'runtime' registered for diagnostics monitoring [monitor] 2018/12/07 05:27:33 'network' registered for diagnostics monitoring [monitor] 2018/12/07 05:27:33 'system' registered for diagnostics monitoring [shard-precreation] 2018/12/07 05:27:33 Starting precreation service with check interval of 10m0s, advance period of 30m0s [snapshot] 2018/12/07 05:27:33 Starting snapshot service [continuous_querier] 2018/12/07 05:27:33 Starting continuous query service [httpd] 2018/12/07 05:27:33 Starting HTTP service [httpd] 2018/12/07 05:27:33 Authentication enabled: false ## heapster [root@master kube-system]# kubectl logs -f heapster-1258036176-sjg7s -n kube-system I1207 05:53:00.275512 1 heapster.go:71] /heapster --source=kubernetes:http://172.16.187.162:8080 --sink=influxdb:http://172.99.39.6:8086 I1207 05:53:00.275568 1 heapster.go:72] Heapster version v1.3.0-beta.1 I1207 05:53:00.275794 1 configs.go:61] Using Kubernetes client with master "http://172.16.187.162:8080" and version v1 I1207 05:53:00.275816 1 configs.go:62] Using kubelet port 10255 I1207 05:53:00.283647 1 influxdb.go:252] created influxdb sink with options: host:172.99.39.6:8086 user:root db:k8s I1207 05:53:00.283680 1 heapster.go:193] Starting with InfluxDB Sink I1207 05:53:00.283687 1 heapster.go:193] Starting with Metric Sink I1207 05:53:00.294214 1 heapster.go:105] Starting heapster on port 8082 I1207 05:54:05.082812 1 influxdb.go:215] Created database "k8s" on influxDB server at "172.99.39.6:8086"

最后查看heapster，因为收集数据须要时间，过一段时间后，查看节点的node的监控数据

[root@master ~]# kubectl top node
NAME             CPU(cores) CPU% MEMORY(bytes) MEMORY% 172.16.187.158 121m 0% 19721Mi 30% 172.16.187.159 112m 0% 15805Mi 24% 172.16.187.160 172m 1% 28090Mi 43%

建立HPA

以上步骤都成功的时候，咱们能够建立HorizontalPodAutoscaler来管理，下面就用ms-wechat来进行测试

apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: ms-wechat  # 名称
  namespace: default #k8s命名空间
spec:
  maxReplicas: 10  # 最大副本数
  minReplicas: 3   # 最小副本数
  scaleTargetRef:   
    apiVersion: apps/v1beta1
    kind: Deployment  
    name: ms-wechat   # 监控名为ms-wechat的Deployment
  targetCPUUtilizationPercentage: 80  # cpu 阈值

查看hpa

[root@master ~]# kubectl get hpa 
NAME        REFERENCE              TARGETS           MINPODS   MAXPODS   REPLICAS   AGE
ms-wechat   Deployment/ms-wechat   <unknown> / 80%   3         10        3          10m

你们看到 targets为unknown有两种缘由

查看原始deployment的resource有没有设置cpu的限制若是没有：kubectl set resources deployment/ms-wechat --limits=cpu=2000m动态设置
等一段时间再查看

查看结果

[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE ms-wechat Deployment/ms-wechat 47% / 80% 3 10 3 11m

能够进行压力测试，观察REPLICAS变化

转载：https://www.jianshu.com/p/31ed5c98648e