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HPA Pod自动扩缩容
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HPA Pod自动扩缩容
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Pod 自动扩缩容
命令创建，如果不知道api类型，可以先创建查看
kubectl run php-apache --image=nginx --requests=cpu=200m --expose --port=80
kubectl autoscale deployment php-apache --cpu-percent=50 --min=1 --max=10
[root@master01 pha]# kubectl get po | grep apach
php-apache-7fd4489764-r2jw6 1/1 Running 0 2m
[root@master01 pha]# kubectl get po php-apache-7fd4489764-r2jw6 -o yaml
apiVersion: v1
kind: Pod
在前面的课程中，我们提到过通过手工执行kubectl scale命令和在Dashboard上操作可以实现Pod的扩缩容，但是这样毕竟需要每次去手工操作一次，而且指不定什么时
候业务请求量就很大了，所以如果不能做到自动化的去扩缩容的话，这也是一个很麻烦的事情。如果Kubernetes系统能够根据Pod当前的负载的变化情况来自动的进行
扩缩容就好了，因为这个过程本来就是不固定的，频繁发生的，所以纯手工的方式不是很现实。
幸运的是Kubernetes为我们提供了这样一个资源对象：Horizontal Pod Autoscaling（Pod水平自动伸缩），简称HPA。HAP通过监控分析RC或者Deployment控制的
所有Pod的负载变化情况来确定是否需要调整Pod的副本数量，这是HPA最基本的原理。
hpa
hpa
HPA在kubernetes集群中被设计成一个controller，我们可以简单的通过kubectl autoscale命令来创建一个HPA资源对象，HPA Controller默认30s轮询一次
（可通过kube-controller-manager的标志--horizontal-pod-autoscaler-sync-period进行设置），查询指定的资源（RC或者Deployment）中Pod的资源使用率，
并且与创建时设定的值和指标做对比，从而实现自动伸缩的功能。
当你创建了HPA后，HPA会从Heapster或者用户自定义的RESTClient端获取每一个一个Pod利用率或原始值的平均值，然后和HPA中定义的指标进行对比，同时计算出需要
伸缩的具体值并进行相应的操作。目前，HPA可以从两个地方获取数据：
Heapster：仅支持CPU使用率
自定义监控：我们到后面的监控的课程中再给大家讲解这部分的使用方法
我们这节课来给大家介绍从Heapster获取监控数据来进行自动扩缩容的方法，所以首先我们得安装Heapster，前面我们在kubeadm搭建集群的课程中，实际上我们已经默
认把Heapster相关的镜像都已经拉取到节点上了，所以接下来我们只需要部署即可，我们这里使用的是Heapster 1.4.2 版本的，前往Heapster的github页面：
https://github.com/kubernetes/heapster
[root@Master ~]# git clone https://github.com/kubernetes/heapster.git
cd /root/heapster/deploy/kube-config/influxdb
sed -i 's@heapster-amd64:v1.5.4@heapster-amd64:v1.4.2@' heapster.yaml
sed -i 's@heapster-grafana-amd64:v5.0.4@heapster-grafana-amd64:v4.4.3@' grafana.yaml
sed -i 's@heapster-influxdb-amd64:v1.5.2@heapster-influxdb-amd64:v1.3.3@' influxdb.yaml
kubectl apply -f .
[root@Master influxdb]# kubectl logs heapster-676cc864c6-k2xvc -n kube-system
E1025 01:37:37.125931 1 reflector.go:190] k8s.io/heapster/metrics/heapster.go:322: Failed to list *v1.Pod: pods is forbidden: User "system:serviceaccount:kube-system:heapster" cannot list pods at the cluster scope
报错：pods is forbidden: cannot list pods at the cluster scope
需要角色权限绑定
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: admin
annotations:
rbac.authorization.kubernetes.io/autoupdate: "true"
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: cluster-admin
subjects:
- kind: ServiceAccount
name: admin
namespace: kube-system
完整的配置如下：
cat << EOF > heapster.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: heapster
namespace: kube-system
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: heapster-admin
annotations:
rbac.authorization.kubernetes.io/autoupdate: "true"
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: cluster-admin
subjects:
- kind: ServiceAccount
name: heapster
namespace: kube-system
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: heapster
namespace: kube-system
spec:
replicas: 1
template:
metadata:
labels:
task: monitoring
k8s-app: heapster
spec:
serviceAccountName: heapster
containers:
- name: heapster
image: k8s.gcr.io/heapster-amd64:v1.4.2
imagePullPolicy: IfNotPresent
command:
- /heapster
- --source=kubernetes:https://kubernetes.default
- --sink=influxdb:http://monitoring-influxdb.kube-system.svc:8086
---
apiVersion: v1
kind: Service
metadata:
labels:
task: monitoring
# For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
# If you are NOT using this as an addon, you should comment out this line.
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: Heapster
name: heapster
namespace: kube-system
spec:
ports:
- port: 80
targetPort: 8082
selector:
k8s-app: heapster
EOF
删除所有
[root@Master influxdb]# kubectl delete -f .
deployment.extensions "monitoring-grafana" deleted
service "monitoring-grafana" deleted
serviceaccount "heapster" deleted
clusterrolebinding.rbac.authorization.k8s.io "heapster-admin" deleted
deployment.extensions "heapster" deleted
service "heapster" deleted
deployment.extensions "monitoring-influxdb" deleted
service "monitoring-influxdb" deleted
创建所有
[root@Master influxdb]# kubectl create -f .
deployment.extensions "monitoring-grafana" created
service "monitoring-grafana" created
serviceaccount "heapster" created
clusterrolebinding.rbac.authorization.k8s.io "heapster-admin" created
deployment.extensions "heapster" created
service "heapster" created
deployment.extensions "monitoring-influxdb" created
service "monitoring-influxdb" created
查看日志
[root@Master influxdb]# kubectl logs -f heapster-676cc864c6-mnxx7 -n kube-system
I1025 02:13:47.418481 1 heapster.go:72] /heapster --source=kubernetes:https://kubernetes.default --sink=influxdb:http://monitoring-influxdb.kube-system.svc:8086
I1025 02:13:47.418533 1 heapster.go:73] Heapster version v1.4.2
I1025 02:13:47.418942 1 configs.go:61] Using Kubernetes client with master "https://kubernetes.default" and version v1
I1025 02:13:47.418960 1 configs.go:62] Using kubelet port 10255
I1025 02:13:47.450524 1 influxdb.go:278] created influxdb sink with options: host:monitoring-influxdb.kube-system.svc:8086 user:root db:k8s
I1025 02:13:47.450549 1 heapster.go:196] Starting with InfluxDB Sink
I1025 02:13:47.450555 1 heapster.go:196] Starting with Metric Sink
I1025 02:13:47.460040 1 heapster.go:106] Starting heapster on port 8082
I1025 02:14:05.071818 1 influxdb.go:241] Created database "k8s" on influxDB server at "monitoring-influxdb.kube-system.svc:8086"
回到dashboard查看,火狐浏览器
https://192.168.224.132:31046
我们将该目录下面的yaml文件保存到我们的集群上，然后使用kubectl命令行工具创建即可，另外创建完成后，如果需要在Dashboard当中看到监控图表，我们还需要在Dashboard中配置上我们的heapster-host。
同样的，我们来创建一个Deployment管理的Nginx Pod，然后利用HPA来进行自动扩缩容。定义Deployment的YAML文件如下：（hpa-demo.yaml）
cat << EOF > hpa-demo.yaml
---
apiVersion: apps/v1beta1
kind: Deployment
metadata:
name: hpa-demo
labels:
app: hpa
spec:
revisionHistoryLimit: 15
minReadySeconds: 5
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 1
template:
metadata:
labels:
app: hpa
spec:
containers:
- name: nginx
image: nginx
resources:
requests:
cpu: "100m"
ports:
- containerPort: 80
EOF
[root@Master ~]# kubectl create -f hpa-demo.yaml
deployment.apps "hpa-demo" created
[root@Master ~]# kubectl get deploy
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
hpa-demo 1 1 1 1 26s
[root@Master ~]# kubectl get po | grep hpa
hpa-demo-6bc5854677-87br2 1/1 Running 0 1m
需要修改kube-controller-manager.yaml配置，使其支持pod自动扩展
查找位置
[root@Master ~]# ps xua | grep kubelet
root 1502 2.8 4.4 766832 78848 ? Ssl 10月24 34:45 /usr/bin/kubelet --bootstrap-kubeconfig=/etc/kubernetes/bootstrap-kubelet.conf --kubeconfig=/etc/kubernetes/kubelet.conf --pod-manifest-path=/etc/kubernetes/manifests --allow-privileged=true --network-plugin=cni --cni-conf-dir=/etc/cni/net.d --cni-bin-dir=/opt/cni/bin --cluster-dns=10.96.0.10 --cluster-domain=cluster.local --authorization-mode=Webhook --client-ca-file=/etc/kubernetes/pki/ca.crt --cadvisor-port=0 --cgroup-driver=cgroupfs --rotate-certificates=true --cert-dir=/var/lib/kubelet/pki --fail-swap-on=false
其中--pod-manifest-path=/etc/kubernetes/manifests 就是放kube-controller-manager.yaml的位置,在对应位置添加
- --horizontal-pod-autoscaler-use-rest-clients=false
具体如下
vim /etc/kubernetes/manifests/kube-controller-manager.yaml
spec:
containers:
- command:
- kube-controller-manager
- --horizontal-pod-autoscaler-use-rest-clients=false
- --address=127.0.0.1
静态pod改了后自动更新，所以不用操作其他
现在我们来创建一个HPA，可以使用kubectl autoscale命令来创建：
[root@Master manifests]# kubectl autoscale deployment hpa-demo --min=1 --max=10 --cpu-percent=5
deployment.apps "hpa-demo" autoscaled
[root@Master manifests]# kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-demo Deployment/hpa-demo <unknown>/5% 1 10 1 54s
查看描述
[root@Master ~]# kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-demo Deployment/hpa-demo 0%/5% 1 10 1 2h
[root@Master ~]# kubectl describe hpa hpa-demo
Name: hpa-demo
Namespace: default
Labels: <none>
Annotations: <none>
CreationTimestamp: Thu, 25 Oct 2018 11:27:44 +0800
Reference: Deployment/hpa-demo
Metrics: ( current / target )
resource cpu on pods (as a percentage of request): 0% (0) / 5%
Min replicas: 1
Max replicas: 10
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale True ReadyForNewScale the last scale time was sufficiently old as to warrant a new scale
ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request)
ScalingLimited True TooFewReplicas the desired replica count is increasing faster than the maximum scale rate
Events: <none>
增加负载，已测试自动扩容
此命令创建了一个关联资源 hpa-demo 的HPA，最小的 pod 副本数为1，最大为10。HPA会根据设定的 cpu使用率（10%）动态的增加或者减少pod数量。
当然出来使用kubectl autoscale命令来创建外，我们依然可以通过创建YAML文件的形式来创建HPA资源对象。如果我们不知道怎么编写的话，可以查看上面命令行创建的HPA的YAML文件：
$ kubectl get hpa hpa-demo -o yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
creationTimestamp: 2017-06-29T08:04:08Z
name: nginxtest
namespace: default
resourceVersion: "951016361"
selfLink: /apis/autoscaling/v1/namespaces/default/horizontalpodautoscalers/nginxtest
uid: 86febb63-5ca1-11e7-aaef-5254004e79a3
spec:
maxReplicas: 5 //资源最大副本数
minReplicas: 1 //资源最小副本数
scaleTargetRef:
apiVersion: extensions/v1beta1
kind: Deployment //需要伸缩的资源类型
name: nginxtest //需要伸缩的资源名称
targetCPUUtilizationPercentage: 50 //触发伸缩的cpu使用率
status:
currentCPUUtilizationPercentage: 48 //当前资源下pod的cpu使用率
currentReplicas: 1 //当前的副本数
desiredReplicas: 2 //期望的副本数
lastScaleTime: 2017-07-03T06:32:19Z
好，现在我们根据上面的YAML文件就可以自己来创建一个基于YAML的HPA描述文件了。
现在我们来增大负载进行测试，我们来创建一个busybox，并且循环访问上面创建的服务。
$ kubectl run -i --tty load-generator --image=busybox /bin/sh
/ # while true; do wget -q -O- http://172.16.255.60; done
下图可以看到，HPA已经开始工作。
$ kubectl get hpa
NAME REFERENCE TARGET CURRENT MINPODS MAXPODS AGE
hpa-demo Deployment/hpa-demo 10% 29% 1 10 27m
[root@Master ~]# kubectl describe hpa hpa-demo
Name: hpa-demo
Namespace: default
Labels: <none>
Annotations: <none>
CreationTimestamp: Thu, 25 Oct 2018 11:27:44 +0800
Reference: Deployment/hpa-demo
Metrics: ( current / target )
resource cpu on pods (as a percentage of request): 26% (26m) / 5%
Min replicas: 1
Max replicas: 10
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale False BackoffBoth the time since the previous scale is still within both the downscale and upscale forbidden windows
ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request)
ScalingLimited True TooManyReplicas the desired replica count is more than the maximum replica count
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal SuccessfulRescale 4m horizontal-pod-autoscaler New size: 4; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 44s horizontal-pod-autoscaler New size: 8; reason: cpu resource utilization (percentage of request) above target
[root@Master ~]# kubectl get po | grep hpa-demo | wc -l
8
同时我们查看相关资源hpa-demo的副本数量，副本数量已经从原来的1变成了3。
$ kubectl get deployment hpa-demo
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
hpa-demo 3 3 3 3 4d
同时再次查看HPA，由于副本数量的增加，使用率也保持在了10%左右。
$ kubectl get hpa
NAME REFERENCE TARGET CURRENT MINPODS MAXPODS AGE
hpa-demo Deployment/hpa-demo 10% 9% 1 10 35m
同样的这个时候我们来关掉busybox来减少负载，然后等待一段时间观察下HPA和Deployment对象
$ kubectl get hpa
NAME REFERENCE TARGET CURRENT MINPODS MAXPODS AGE
hpa-demo Deployment/hpa-demo 10% 0% 1 10 48m
$ kubectl get deployment hpa-demo
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
hpa-demo 1 1 1 1 4d
可以看到副本数量已经由3变为1。
不过当前的HPA只有CPU使用率这一个指标，还不是很灵活的，在后面的课程中我们来根据我们自定义的监控来自动对Pod进行扩缩容。
kubectl autoscale deployment hpa-demo --min=1 --max=10 --cpu-percent=5
该命令等价于
[root@Master ~]# kubectl get hpa hpa-demo -o yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: hpa-demo
namespace: default
spec:
maxReplicas: 10
minReplicas: 1
scaleTargetRef:
apiVersion: extensions/v1beta1
kind: Deployment
name: hpa-demo
targetCPUUtilizationPercentage: 5
完整hpa的yaml示例
cat << EOF > hpa-demo.yaml
---
apiVersion: apps/v1beta1
kind: Deployment
metadata:
name: hpa-demo
labels:
app: hpa
spec:
revisionHistoryLimit: 15
minReadySeconds: 5
strategy:
type: RollingUpdate
rollingUpdate:
maxSurge: 1
maxUnavailable: 1
template:
metadata:
labels:
app: hpa
spec:
containers:
- name: nginx
image: nginx
resources:
requests:
cpu: 100m
ports:
- containerPort: 80
---
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: hpa-demo
namespace: default
spec:
maxReplicas: 10
minReplicas: 1
scaleTargetRef:
apiVersion: extensions/v1beta1
kind: Deployment
name: hpa-demo
targetCPUUtilizationPercentage: 5
EOF
重新部署一次
删除原来的
[root@Master ~]# kubectl delete -f hpa-demo.yaml
deployment.apps "hpa-demo" deleted
[root@Master ~]# kubectl delete hpa hpa-demo
horizontalpodautoscaler.autoscaling "hpa-demo" deleted
[root@Master ~]# kubectl create -f hpa-demo.yaml
deployment.apps "hpa-demo" created
horizontalpodautoscaler.autoscaling "hpa-demo" created
检查
[root@Master ~]# kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
hpa-demo Deployment/hpa-demo 0%/5% 1 10 1 3m