目录
一、概述
二、安装部署Metrics-Server组件
1.下载Metrics-Server资源清单
2.编辑Metrics-Server的资源清单
3.验证Metrics-Server是否成功安装
4.使用top命令测试是否管用
三、hpa资源实现pod水平伸缩（自动扩缩容）
1.编写deploy资源清单
2.编写hpa资源清单
3.查看hpa资源
四、压测
1.进入pod，安装和使用stress工具
2.查看hpa资源的负载情况
一、概述
Metrics-Server组件目的：获取集群中pod、节点等负载信息；
hpa资源目的：通过metrics-server获取的pod负载信息，自动伸缩创建pod；
参考链接：
资源指标管道 | Kubernetes
https://github.com/kubernetes/kubernetes/tree/master/cluster/addons/metrics-server
GitHub - kubernetes-sigs/metrics-server: Scalable and efficient source of container resource metrics for Kubernetes built-in autoscaling pipelines.
二、安装部署Metrics-Server组件
就是给k8s集群安装top命令的意思；
1.下载Metrics-Server资源清单
[root@k8s1 k8s]# wget https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/high-availability-1.21+.yaml
2.编辑Metrics-Server的资源清单
[root@k8s1 k8s]# vim high-availability-1.21+.yamlapiVersion: v1
kind: ServiceAccount
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:labels:k8s-app: metrics-serverrbac.authorization.k8s.io/aggregate-to-admin: "true"rbac.authorization.k8s.io/aggregate-to-edit: "true"rbac.authorization.k8s.io/aggregate-to-view: "true"name: system:aggregated-metrics-reader
rules:
- apiGroups:- metrics.k8s.ioresources:- pods- nodesverbs:- get- list- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:labels:k8s-app: metrics-servername: system:metrics-server
rules:
- apiGroups:- ""resources:- nodes/metricsverbs:- get
- apiGroups:- ""resources:- pods- nodesverbs:- get- list- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:labels:k8s-app: metrics-servername: metrics-server-auth-readernamespace: kube-system
roleRef:apiGroup: rbac.authorization.k8s.iokind: Rolename: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccountname: metrics-servernamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:labels:k8s-app: metrics-servername: metrics-server:system:auth-delegator
roleRef:apiGroup: rbac.authorization.k8s.iokind: ClusterRolename: system:auth-delegator
subjects:
- kind: ServiceAccountname: metrics-servernamespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:labels:k8s-app: metrics-servername: system:metrics-server
roleRef:apiGroup: rbac.authorization.k8s.iokind: ClusterRolename: system:metrics-server
subjects:
- kind: ServiceAccountname: metrics-servernamespace: kube-system
---
apiVersion: v1
kind: Service
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
spec:ports:- name: httpsport: 443protocol: TCPtargetPort: httpsselector:k8s-app: metrics-server
---
apiVersion: apps/v1
kind: Deployment
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
spec:replicas: 2selector:matchLabels:k8s-app: metrics-serverstrategy:rollingUpdate:maxUnavailable: 1template:metadata:labels:k8s-app: metrics-serverspec:affinity:podAntiAffinity:requiredDuringSchedulingIgnoredDuringExecution:- labelSelector:matchLabels:k8s-app: metrics-servernamespaces:- kube-systemtopologyKey: kubernetes.io/hostnamecontainers:- args:#启动允许使用不安全的证书- --kubelet-insecure-tls- --cert-dir=/tmp- --secure-port=10250- --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname- --kubelet-use-node-status-port- --metric-resolution=15s#image: registry.k8s.io/metrics-server/metrics-server:v0.7.1image: registry.aliyuncs.com/google_containers/metrics-server:v0.6.3imagePullPolicy: IfNotPresentlivenessProbe:failureThreshold: 3httpGet:path: /livezport: httpsscheme: HTTPSperiodSeconds: 10name: metrics-serverports:- containerPort: 10250name: httpsprotocol: TCPreadinessProbe:failureThreshold: 3httpGet:path: /readyzport: httpsscheme: HTTPSinitialDelaySeconds: 20periodSeconds: 10resources:requests:cpu: 100mmemory: 200MisecurityContext:allowPrivilegeEscalation: falsecapabilities:drop:- ALLreadOnlyRootFilesystem: truerunAsNonRoot: truerunAsUser: 1000seccompProfile:type: RuntimeDefaultvolumeMounts:- mountPath: /tmpname: tmp-dirnodeSelector:kubernetes.io/os: linuxpriorityClassName: system-cluster-criticalserviceAccountName: metrics-servervolumes:- emptyDir: {}name: tmp-dir
---
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:labels:k8s-app: metrics-servername: metrics-servernamespace: kube-system
spec:minAvailable: 1selector:matchLabels:k8s-app: metrics-server
---
apiVersion: apiregistration.k8s.io/v1
kind: APIService
metadata:labels:k8s-app: metrics-servername: v1beta1.metrics.k8s.io
spec:group: metrics.k8s.iogroupPriorityMinimum: 100insecureSkipTLSVerify: trueservice:name: metrics-servernamespace: kube-systemversion: v1beta1versionPriority: 100[root@k8s1 k8s]# kubectl apply -f high-availability-1.21+.yaml
3.验证Metrics-Server是否成功安装
4.使用top命令测试是否管用
[root@k8s1 k8s]# kubectl top node
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
k8s1 734m 18% 867Mi 11%
k8s2 118m 2% 493Mi 6%
[root@k8s1 k8s]# kubectl top pods -A
NAMESPACE NAME CPU(cores) MEMORY(bytes)
default dm01-7875cdc8b4-4lb62 0m 4Mi
default dm01-7875cdc8b4-mt7hs 0m 2Mi
default dm01-7875cdc8b4-zv94k 0m 2Mi
kube-flannel kube-flannel-ds-jg8nq 7m 20Mi
kube-flannel kube-flannel-ds-scx6p 7m 22Mi
kube-system coredns-6d8c4cb4d-55v2q 2m 18Mi
kube-system coredns-6d8c4cb4d-khrbf 2m 18Mi
kube-system etcd-k8s1 14m 66Mi
kube-system kube-apiserver-k8s1 55m 175Mi
kube-system kube-controller-manager-k8s1 18m 50Mi
kube-system kube-proxy-lsjgc 1m 19Mi
kube-system kube-proxy-vfbqr 1m 17Mi
kube-system kube-scheduler-k8s1 4m 21Mi
kube-system metrics-server-dfb9648d6-2fcng 4m 19Mi
kube-system metrics-server-dfb9648d6-4l85l 4m 22Mi 三、hpa资源实现pod水平伸缩（自动扩缩容）
- 当资源使用超一定的范围，会自动扩容，但是扩容数量不会超过最大pod数量；
- 扩容时无延迟，只要监控资源使用超过阔值，则会直接创建pod；
- 当资源使用率恢复到阔值以下时，需要等待一段时间才会释放，大概时5分钟；
1.编写deploy资源清单
[root@k8s1 k8s]# cat deploy.yaml
apiVersion: apps/v1
kind: Deployment
metadata:name: dm-hpa
spec:replicas: 1selector:matchLabels:k8s: osleetemplate:metadata:labels:k8s: osleespec:containers:- name: c1image: centos:7command:- tail- -f- /etc/hostsresources:requests:cpu: "50m"limits:cpu: "150m"[root@k8s1 k8s]# kubectl apply -f deploy.yaml
deployment.apps/dm-hpa created
2.编写hpa资源清单
[root@k8s1 k8s]# cat hpa.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:name: hpa-tools
spec:#指定pod最大的数量是多少（自动扩容的上限）maxReplicas: 10#指定pod最小的pod数量是多少（自动缩容的下限）minReplicas: 2#弹性伸缩引用的目标是谁？scaleTargetRef:#目标资源的apiapiVersion: "apps/v1"#目标资源的类型kindkind: Deployment#目标资源的名称metadata-name是什么name: dm-hpa#使用cpu阈值（使用到达多少，开始扩容、缩容）#95%targetCPUUtilizationPercentage: 95[root@k8s1 k8s]# kubectl apply -f hpa.yaml
horizontalpodautoscaler.autoscaling/hpa-tools created
3.查看hpa资源
[root@k8s1 k8s]# kubectl get hpa -o wide
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-tools Deployment/dm-hpa 0%/95% 2 10 2 102s
四、压测
1.进入pod，安装和使用stress工具
# 进入pod容器
[root@k8s1 k8s]# kubectl exec -it pod/dm-hpa-844c748565-jpzxt -- sh
sh-4.2# yum -y install wget# 安装aili源和epel源
sh-4.2# wget -O /etc/yum.repos.d/CentOS-Base.repo https://mirrors.aliyun.com/repo/Centos-7.repo
sh-4.2# wget -O /etc/yum.repos.d/epel.repo https://mirrors.aliyun.com/repo/epel-7.repo# 安装压测工具
sh-4.2# yum -y install stress# 开始使用命令压测pod
sh-4.2# stress --cpu 8 --io 4 --vm 2 --vm-bytes 128M --timeout 20m2.查看hpa资源的负载情况
[root@k8s1 ~]# kubectl get hpa -o wide
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-tools Deployment/dm-hpa 100%/95% 2 10 3 11m
[root@k8s1 ~]# kubectl get pod
NAME READY STATUS RESTARTS AGE
dm-hpa-844c748565-jbn7s 1/1 Running 0 7m17s
dm-hpa-844c748565-jpzxt 1/1 Running 0 11m
dm-hpa-844c748565-tn8fr 1/1 Running 0 24m
可以看到：
- 我们创建的deploy资源只有一个副本；
- 我们创建的hpa资源之后，设置最小值是2，最大值是10 ；
- 我们在查看pod，可以看见，pod变成了2个；
- 我们进入容器，开始压测，将负载压测到超过95%；
- 再次查看pod，发现变成了3个，自动创建了一个；
- 关闭压测，5分钟后，pod有回归到了2个；
- 至此，hpa的pod自动伸缩，测试完毕；
