HPA（Horizontal Pod Autoscaler）是kubernetes的一种资源对象，能够根据某些指标对在statefulSet、replicaController、replicaSet等集合中的pod数量进行动态伸缩，使运行在上面的服务对指标的变化有一定的自适应能力。
安装metric-server
确保安装metric-server，可以检测到集群的CPU和内存信息。
---
apiVersion: apiregistration.k8s.io/v1beta1
kind: APIService
metadata:
name: v1beta1.metrics.k8s.io
spec:
service:
name: metrics-server
namespace: kube-system
group: metrics.k8s.io
version: v1beta1
insecureSkipTLSVerify: true
groupPriorityMinimum: 100
versionPriority: 100
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: metrics-server
namespace: kube-system
labels:
k8s-app: metrics-server
spec:
selector:
matchLabels:
k8s-app: metrics-server
strategy:
rollingUpdate:
maxUnavailable: 0
template:
metadata:
name: metrics-server
labels:
k8s-app: metrics-server
spec:
serviceAccountName: metrics-server
volumes:
# mount in tmp so we can safely use from-scratch images and/or read-only containers
- name: tmp-dir
emptyDir: {}
containers:
- name: metrics-server
image: gcr.io/k8s-staging-metrics-server/metrics-server:master
imagePullPolicy: IfNotPresent
command:
- /metrics-server
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP,ExternalIP,Hostname
args:
- --cert-dir=/tmp
- --secure-port=4443
ports:
- name: main-port
containerPort: 4443
protocol: TCP
readinessProbe:
httpGet:
path: /healthz
port: main-port
scheme: HTTPS
securityContext:
readOnlyRootFilesystem: true
runAsNonRoot: true
runAsUser: 1000
volumeMounts:
- name: tmp-dir
mountPath: /tmp
nodeSelector:
kubernetes.io/os: linux
---
apiVersion: policy/v1beta1
kind: PodDisruptionBudget
metadata:
name: metrics-server
namespace: kube-system
labels:
k8s-app: metrics-server
spec:
minAvailable: 100%
selector:
matchLabels:
k8s-app: metrics-server
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: system:aggregated-metrics-reader
labels:
rbac.authorization.k8s.io/aggregate-to-view: "true"
rbac.authorization.k8s.io/aggregate-to-edit: "true"
rbac.authorization.k8s.io/aggregate-to-admin: "true"
rules:
- apiGroups: ["metrics.k8s.io"]
resources: ["pods", "nodes"]
verbs: ["get", "list", "watch"]
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: metrics-server
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: metrics-server-auth-reader
namespace: kube-system
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: metrics-server:system:auth-delegator
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:auth-delegator
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: system:metrics-server
rules:
- apiGroups:
- ""
resources:
- pods
- nodes
- nodes/stats
- namespaces
- configmaps
verbs:
- get
- list
- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: system:metrics-server
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:metrics-server
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
---
apiVersion: v1
kind: Service
metadata:
name: metrics-server
namespace: kube-system
labels:
kubernetes.io/name: "Metrics-server"
kubernetes.io/cluster-service: "true"
spec:
selector:
k8s-app: metrics-server
ports:
- port: 443
protocol: TCP
targetPort: main-port
安装完成后可以通过kubectl top命令查看相应资源的CPU和内存使用情况
root@master01:~/yaml/hpa/WebBench# kubectl top node
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
master01 390m 19% 2218Mi 57%
worker01 89m 4% 1744Mi 45%
worker02 1093m 54% 1536Mi 39%
root@master01:~/yaml/hpa/WebBench# kubectl top pod
NAME CPU(cores) MEMORY(bytes)
nfs-client-provisioner-6565b468fc-h46kx 2m 7Mi
nginx-59f6b957d7-5kjph 0m 1Mi
部署服务
部署一个Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: nginx
labels:
app: nginx
spec:
replicas: 1
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- name: nginx
image: nginx:1.7.6
imagePullPolicy: IfNotPresent
ports:
- containerPort: 80
resources:
requests:
cpu: "100m"
暴露这个服务
root@master01:~/yaml/hpa# kubectl expose deployment nginx --port=80
service/nginx exposed
配置HPA
配置autoscale策略，Pod最大数量为10，最小数量为1，在cpu使用率超过80%的时候扩缩容。
root@master01:~/yaml/hpa# kubectl autoscale deployment nginx --max=10 --min=1 --cpu-percent=80
horizontalpodautoscaler.autoscaling/nginx autoscaled
测试验证
部署一个测试工具，用于发送请求
apt-get -y install gcc
git clone https://github.com/EZLippi/WebBench.git
cd WebBench
make ; make install
root@master01:~/yaml/hpa/WebBench# webbench -c 1000 -t 60 http://10.103.27.138/ #ip地址是service的ip
Webbench - Simple Web Benchmark 1.5
Copyright (c) Radim Kolar 1997-2004, GPL Open Source Software.
Request:
GET / HTTP/1.0
User-Agent: WebBench 1.5
Host: 10.103.27.138
Runing info: 1000 clients, running 60 sec.
Speed=220372 pages/min, 3098478 bytes/sec.
Requests: 220271 susceed, 101 failed.
可以看到Pod自动扩容了
Every 1.0s: kubectl get hpa && kubectl top pod && kubectl get pod Sun May 10 15:06:45 2020
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
nginx Deployment/nginx 558%/80% 1 10 7 14m
NAME CPU(cores) MEMORY(bytes)
nginx-59f6b957d7-rr7zv 558m 1Mi
NAME READY STATUS RESTARTS AGE
nginx-59f6b957d7-5kjph 1/1 Running 0 49s
nginx-59f6b957d7-67q9n 1/1 Running 0 49s
nginx-59f6b957d7-fzqnn 1/1 Running 0 33s
nginx-59f6b957d7-gqmc4 1/1 Running 0 49s
nginx-59f6b957d7-k9b78 1/1 Running 0 34s
nginx-59f6b957d7-r52x9 1/1 Running 0 33s
nginx-59f6b957d7-rr7zv 1/1 Running 0 15m
