内容简介：Horizontal Pod Autoscaling，简称HPA，是Kubernetes中实现POD水平自动伸缩的功能。K8S集群可以通过Replication Controller的scale机制完成服务的扩容或缩容，实现具有伸缩性的服务。K8S自动伸缩分为：
Horizontal Pod Autoscaling，简称HPA，是Kubernetes中实现POD水平自动伸缩的功能。
简介
K8S集群可以通过Replication Controller的scale机制完成服务的扩容或缩容，实现具有伸缩性的服务。
K8S自动伸缩分为：
- sacle手动伸缩。见 k8s滚动升级(RollingUpdate)
- autoscale自动伸缩，见HPA。
自动扩展主要分为两种：
- 水平扩展(scale out)，针对于实例数目的增减。
- 垂直扩展(scal up)，即单个实例可以使用的资源的增减, 比如增加cpu和增大内存。
HPA属于前者。它可以根据CPU使用率或应用自定义metrics自动扩展Pod数量(支持 replication controller、deployment 和 replica set)。
获取metrics的两种方式：
- Heapster：heapster提供metrics服务，但是在v1(autoscaling/v1)版本中仅支持以CPU作为扩展度量指标。而其他比如：内存，网络流量，qps等目前处于beta阶段(autoscaling/v2beta1)。
- Cousom：同样处于beta阶段(autoscaling/v2beta1)，但是涉及到自定义的REST API的开发，复杂度会大一些，并且当需要从自定义的监控中获取数据时，只能设置绝对值，无法设置使用率。
工作流程
- 创建HPA资源，设定目标CPU使用率限额，以及最大/最小实例数，一定要设置Pod的资源限制参数:
request，否则HPA不会工作。 - 控制管理器每隔30s(在
kube-controller-manager.service中可以通过–horizontal-pod-autoscaler-sync-period修改)查询metrics的资源使用情况。 - 然后与创建时设定的值和指标做对比(平均值之和/限额)，求出目标调整的实例个数。
- 目标调整的实例数不能超过第一条中设定的最大/最小实例数。如果没有超过，则扩容；超过，则扩容至最大的实例个数。
- 重复第2-4步。
自动伸缩算法
HPA Controller会通过调整副本数量使得CPU使用率尽量向期望值靠近，而且不是完全相等。另官方考虑到自动扩展的决策可能需要一段时间才会生效：例如当pod所需要的CPU负荷过大，从而在创建一个新pod的过程中，系统的CPU使用量可能会同样在有一个攀升的过程。所以在每一次作出决策后的一段时间内，将不再进行扩展决策。对于扩容而言，这个时间段为3分钟，缩容为5分钟(可以通过 --horizontal-pod-autoscaler-downscale-delay ， --horizontal-pod-autoscaler-upscale-delay 进行调整)。
- HPA Controller中有一个tolerance（容忍力）的概念，它允许一定范围内的使用量的不稳定，现在默认为0.1，这也是出于维护系统稳定性的考虑。例如设定HPA调度策略为cpu使用率高于50%触发扩容，那么只有当使用率大于55%或者小于45%才会触发伸缩活动，HPA会尽力把Pod的使用率控制在这个范围之间。
- 具体的每次扩容或者缩容的多少Pod的算法为：Ceil(前采集到的使用率 / 用户自定义的使用率) * Pod数量)。
- 每次最大扩容pod数量不会超过当前副本数量的2倍。
环境说明
| 角色 | IP | 操作系统版本 |
|---|---|---|
| master | 192.168.1.201 | centos 7.4 |
| etcd1 | 192.168.1.201 | centos 7.4 |
| etcd2 | 192.168.1.202 | centos 7.4 |
| etcd3 | 192.168.1.203 | centos 7.4 |
| node1 | 192.168.1.204 | centos 7.4 |
| node2 | 192.168.1.205 | centos 7.4 |
| 环境 | 软件版本 |
|---|---|
| kubectl server | v1.9.2 |
| kubectl client | v1.9.2 |
| Go | go1.9.2 |
| etcdctl | 3.2.15 |
| etcd | 3.2.15 |
| flanneld | v0.10.0 |
| cfssl | 1.2.0 |
| docker | 18.09.1-beta1 |
[root@master ~]# kubectl cluster-info Kubernetes master is running at https://192.168.1.201:6443 Heapster is running at https://192.168.1.201:6443/api/v1/namespaces/kube-system/services/heapster/proxy monitoring-grafana is running at https://192.168.1.201:6443/api/v1/namespaces/kube-system/services/monitoring-grafana/proxy monitoring-influxdb is running at https://192.168.1.201:6443/api/v1/namespaces/kube-system/services/monitoring-influxdb/proxy To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'. [root@master ~]#
[root@master ~]# kubectl -s http://192.168.1.201:8080 get componentstatuses
NAME STATUS MESSAGE ERROR
controller-manager Healthy ok
etcd-2 Healthy {"health": "true"}
etcd-1 Healthy {"health": "true"}
scheduler Healthy ok
etcd-0 Healthy {"health": "true"}
[root@master ~]#
[root@master ~]# kubectl get nodes NAME STATUS ROLES AGE VERSION 192.168.1.204 Ready <none> 21h v1.9.2 192.168.1.205 Ready <none> 21h v1.9.2 [root@master ~]#
部署HPA
先准备一套K8S集群环境，环境部署略。
创建Deployment POD应用nginx
[root@master ~]# cat nginx.yml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: nginx
spec:
replicas: 1
template:
metadata:
labels:
app: nginx-hpa
spec:
containers:
- name: nginx
image: nginx:latest
ports:
- containerPort: 80
name: http
protocol: TCP
resources:
requests:
cpu: 0.01
memory: 25Mi
limits:
cpu: 0.05
memory: 60Mi
---
apiVersion: v1
kind: Service
metadata:
name: nginx
labels:
app: nginx-hpa
spec:
selector:
app: nginx-hpa
type: NodePort
ports:
- name: http
protocol: TCP
port: 80
targetPort: 80
nodePort: 30080
[root@master ~]#
[root@master ~]# kubectl apply -f nginx.yml [root@master ~]# kubectl get pod -o wide NAME READY STATUS RESTARTS AGE IP NODE nginx-5dcf548595-bk9cr 1/1 Running 1 14h 172.30.94.2 192.168.1.205 [root@master ~]#
创建nginx应用的HPA
[root@master ~]# cat nginx-hpa-cpu.yml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: nginx-hpa
spec:
scaleTargetRef:
apiVersion: extensions/v1beta1
kind: Deployment
name: nginx
minReplicas: 1
maxReplicas: 5
targetCPUUtilizationPercentage: 70
[root@master ~]#
[root@master ~]# kubectl apply -f nginx-hpa-cpu.yml [root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx <unknown> / 70% 1 5 1 14h [root@master ~]#
Q1
这时发现nginx-hpa获取不到当前的CPU情况（TARGETS）。等待几分钟后执行 kubectl describe hpa 发现HPA报错信息如下：
[root@master ~]# kubectl describe hpa
Name: nginx-hpa
Namespace: default
Labels: <none>
Annotations: kubectl.kubernetes.io/last-applied-configuration={"apiVersion":"au
toscaling/v1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"nginx-hpa","namespace":"default"},"spec":{"maxReplic...
CreationTimestamp: Sat, 26 Jan 2019 22:23:08 +0800
Reference: Deployment/nginx
Metrics: ( current / target )
resource cpu on pods (as a percentage of request): <unknown> / 70%
Min replicas: 1
Max replicas: 5
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale True SucceededGetScale the HPA controller was able to get the target's current scale
ScalingActive False FailedGetResourceMetric the HPA was unable to compute the replica count: unable to get metrics for resource cpu: unable to fetch metrics from API: the server could not find the requested resource (get pods.metrics.k8s.io)
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning FailedComputeMetricsReplicas 1m (x12 over 3m) horizontal-pod-autoscaler failed to get cpu utilization: unable to get metrics for resource cpu: unable to fetch metrics from API: the server could not find the requested resource (get pods.metrics.k8s.io)
Warning FailedGetResourceMetric 1m (x13 over 3m) horizontal-pod-autoscaler unable to get metrics for resource cpu: unable to fetch metrics from API: the server could not find the requested resource (get pods.metrics.k8s.io)
[root@master ~]#
大概意思是HPA无法通过API获取到metrics值。
解决办法：
在 /etc/systemd/system/kube-controller-manager.service 配置文件中新增 --horizontal-pod-autoscaler-use-rest-clients=false 配置参数。然后重启kube-controller-manager服务即可。
kube-controller-manager's parameter --horizontal-pod-autoscaler-use-rest-clients in k8s 1.9.0 default value is true , while in k8s 1.8.x is false change it to false and it works.
[root@master ~]# cat /etc/systemd/system/kube-controller-manager.service [Unit] Description=Kubernetes Controller Manager Documentation=https://github.com/GoogleCloudPlatform/kubernetes [Service] ExecStart=/usr/local/k8s/bin/kube-controller-manager \ --address=127.0.0.1 \ --master=http://192.168.1.201:8080 \ --allocate-node-cidrs=true \ --service-cluster-ip-range=172.16.0.0/16 \ --cluster-cidr=172.30.0.0/16 \ --cluster-name=kubernetes \ --cluster-signing-cert-file=/etc/kubernetes/ssl/ca.pem \ --cluster-signing-key-file=/etc/kubernetes/ssl/ca-key.pem \ --service-account-private-key-file=/etc/kubernetes/ssl/ca-key.pem \ --root-ca-file=/etc/kubernetes/ssl/ca.pem \ --leader-elect=true \ --horizontal-pod-autoscaler-use-rest-clients=false \ --v=2 Restart=on-failure RestartSec=5 [Install] WantedBy=multi-user.target [root@master ~]#
[root@master ~]# systemctl daemon-reload [root@master ~]# systemctl restart kube-controller-manager
Q2
配置并重启完成kube-controller-manager服务后，执行 kubectl delete -f nginx-hpa-cpu.yml 和 kubectl apply -f nginx-hpa-cpu.yml 重新创建服务后，发现出现新的错误，信息如下：
[root@master ~]# kubectl describe hpa
Name: nginx-hpa
Namespace: default
Labels: <none>
Annotations: kubectl.kubernetes.io/last-applied-configuration={"apiVersion":"au
scaling/v1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"nginx-hpa","namespace":"default"},"spec{"maxRepl...
CreationTimestamp: Sun, 27 Jan 2019 00:18:02 +0800
Reference: Deployment/nginx
Metrics: ( current / target )
resource cpu on pods (as a percentage of request): <unknown> / 70%
Min replicas: 1
Max replicas: 5
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale True SucceededGetScale the HPA controller was able to get the target's current scale
ScalingActive False FailedGetResourceMetric the HPA was unable to compute the replica count: unable to get metrics r resource cpu: failed to get pod resource metrics: an error on the server ("Error: 'dial tcp 172.30.9.4:8082: getsockoptconnection timed out'\nTrying to reach: 'http://172.30.9.4:8082/apis/metrics/v1alpha1/namespaces/default/pods?labelSelect=app%3Dnginx-hpa'") has prevented the request from succeeding (get services http:heapster:)
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning FailedUpdateStatus 2m horizontal-pod-autoscaler Operation cannot be fulfilled on hozontalpodautoscalers.autoscaling "nginx-hpa": the object has been modified; please apply your changes to the latest versi and try again
Warning FailedGetResourceMetric 24s (x3 over 4m) horizontal-pod-autoscaler unable to get metrics for resource u: failed to get pod resource metrics: an error on the server ("Error: 'dial tcp 172.30.9.4:8082: getsockopt: connection med out'\nTrying to reach: 'http://172.30.9.4:8082/apis/metrics/v1alpha1/namespaces/default/pods?labelSelector=app%3Dnginhpa'") has prevented the request from succeeding (get services http:heapster:)
Warning FailedComputeMetricsReplicas 24s (x3 over 4m) horizontal-pod-autoscaler failed to get cpu utilization: unab to get metrics for resource cpu: failed to get pod resource metrics: an error on the server ("Error: 'dial tcp 172.30.9.4:8082: getsockopt: connection timed out'\nTrying to reach: 'http://172.30.9.4:8082/apis/metrics/v1alpha1/namespaces/defaulpods?labelSelector=app%3Dnginx-hpa'") has prevented the request from succeeding (get services http:heapster:)
[root@master ~]#
意思是HPA无法连接heapster服务。于是检查heapster服务是否异常。
[root@master ~]# kubectl get pod -o wide -n kube-system NAME READY STATUS RESTARTS AGE IP NODE heapster-6d5c495969-2rgcr 1/1 Running 2 20h 172.30.9.4 192.168.1.204 kubernetes-dashboard-cbbf9945c-bkvbk 1/1 Running 2 20h 172.30.9.3 192.168.1.204 monitoring-grafana-67d68bf9c6-zv928 1/1 Running 2 20h 172.30.9.2 192.168.1.204 monitoring-influxdb-7c4c46745f-kbxgb 1/1 Running 0 <invalid> 172.30.9.5 192.168.1.204 [root@master ~]#
访问kube-dashboard发现POD是可以通过heapster获取到CPU内存的信息的。如下，说明heapster工作正常。
于是到node节点手动curl访问连接异常的URL。经测试在node1节点上访问正常。
[root@node1 ~]# curl 'http://172.30.9.4:8082/apis/metrics/v1alpha1/namespaces/default/pods?labelSelector=app%3Dnginx-hpa'
{
"metadata": {},
"items": [
{
"metadata": {
"name": "nginx-5dcf548595-bk9cr",
"namespace": "default",
"creationTimestamp": "2019-01-27T07:29:43Z"
},
"timestamp": "2019-01-27T07:29:00Z",
"window": "1m0s",
"containers": [
{
"name": "nginx",
"usage": {
"cpu": "0",
"memory": "2820Ki"
}
}
]
}
]
}
[root@node1 ~]#
于是到kube-master上访问测试，发现HPA无法访问到heapster。
[root@master ~]# curl 'http://172.30.9.4:8082/apis/metrics/v1alpha1/namespaces/default/pods?labelSelector=app%3Dnginx-hpa' curl: (7) Failed connect to 172.30.9.4:8082; Connection timed out [root@master ~]#
接下来我们来测试下网络情况，发现kube-master无法Ping通heapster的POD地址。
[root@master ~]# ping 172.30.9.4 PING 172.30.9.4 (172.30.9.4) 56(84) bytes of data. ^C --- 172.30.9.4 ping statistics --- 2 packets transmitted, 0 received, 100% packet loss, time 1002ms [root@master ~]# telnet 172.30.9.4 8082 Trying 172.30.9.4... telnet: connect to address 172.30.9.4: Connection timed out [root@master ~]#
测试发现是网络不通导致的。解决办法是在kube-master上安装flannel网络。
如果flannel网络的IP地址丢失，重启flannel网卡 systemctl restart flanneld 即可解决。
[root@localhost ~]# ip a
1: lo: <LOOPBACK,UP,LOWER_UP> mtu 65536 qdisc noqueue state UNKNOWN qlen 1
link/loopback 00:00:00:00:00:00 brd 00:00:00:00:00:00
inet 127.0.0.1/8 scope host lo
valid_lft forever preferred_lft forever
inet6 ::1/128 scope host
valid_lft forever preferred_lft forever
2: ens33: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1500 qdisc pfifo_fast state UP qlen 1000
link/ether 00:0c:29:48:f6:1d brd ff:ff:ff:ff:ff:ff
inet 192.168.1.201/24 brd 192.168.1.255 scope global ens33
valid_lft forever preferred_lft forever
inet6 fe80::22d8:9dda:6705:ec09/64 scope link
valid_lft forever preferred_lft forever
3: flannel.1: <BROADCAST,MULTICAST,UP,LOWER_UP> mtu 1450 qdisc noqueue state UNKNOWN
link/ether 6e:05:c0:9c:34:3f brd ff:ff:ff:ff:ff:ff
inet 172.30.13.0/32 scope global flannel.1
valid_lft forever preferred_lft forever
inet6 fe80::6c05:c0ff:fe9c:343f/64 scope link
valid_lft forever preferred_lft forever
[root@localhost ~]#
再测试下kube-master到heapster POD的网络情况：
[root@master ~]# ping 172.30.9.4 -c 4 PING 172.30.9.4 (172.30.9.4) 56(84) bytes of data. 64 bytes from 172.30.9.4: icmp_seq=1 ttl=63 time=2.15 ms 64 bytes from 172.30.9.4: icmp_seq=2 ttl=63 time=1.27 ms 64 bytes from 172.30.9.4: icmp_seq=3 ttl=63 time=1.30 ms 64 bytes from 172.30.9.4: icmp_seq=4 ttl=63 time=1.66 ms --- 172.30.9.4 ping statistics --- 4 packets transmitted, 4 received, 0% packet loss, time 3003ms rtt min/avg/max/mdev = 1.277/1.599/2.150/0.354 ms [root@master ~]# telnet 172.30.9.4 8082 Trying 172.30.9.4... telnet: connect to address 172.30.9.4: Connection refused [root@master ~]#
重新导入nginx-hpa-cpu.yml文件，然后等待几分钟…
[root@localhost ~]# kubectl delete -f nginx-hpa-cpu.yml horizontalpodautoscaler "nginx-hpa" deleted [root@localhost ~]# [root@localhost ~]# kubectl apply -f nginx-hpa-cpu.yml horizontalpodautoscaler "nginx-hpa" created [root@localhost ~]#
OK，HPA连接heapster成功。
[root@localhost ~]# kubectl get hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
nginx-hpa Deployment/nginx 0% / 70% 1 5 1 39s
[root@localhost ~]#
[root@localhost ~]# kubectl describe hpa
Name: nginx-hpa
Namespace: default
Labels: <none>
Annotations: kubectl.kubernetes.io/last-applied-configuration={"apiVersion":"au
toscaling/v1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"nginx-hpa","namespace":"default"},"spec":{"maxRepl...
CreationTimestamp: Sun, 27 Jan 2019 01:04:25 +0800
Reference: Deployment/nginx
Metrics: ( current / target )
resource cpu on pods (as a percentage of request): 0% (0) / 70%
Min replicas: 1
Max replicas: 5
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 succesfully 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>
[root@localhost ~]#
HPA测试
截至目前，HPA支持的API版本有三个。分别是 autoscaling/v1 ， autoscaling/v2beta1 ， autoscaling/v2beta2 。其中 autoscaling/v1 只支持CPU一种伸缩指标；在 autoscaling/v2beta1 中增加支持custom metrics；在 autoscaling/v2beta2 中增加支持external metrics。
详细说明参考：
官方说明，在k8s 1.11版本，HPA将不再从heapster上获取指标。
The HorizontalPodAutoscaler normally fetches metrics from a series of aggregated APIs (metrics.k8s.io, custom.metrics.k8s.io, and external.metrics.k8s.io). The metrics.k8s.io API is usually provided by metrics-server, which needs to be launched separately. See metrics-server for instructions. The HorizontalPodAutoscaler can also fetch metrics directly from Heapster. Note: FEATURE STATE: Kubernetes 1.11 deprecated Fetching metrics from Heapster is deprecated as of Kubernetes 1.11.
autoscaling/v1
[root@master ~]# cat nginx-hpa-cpu.yml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: nginx-hpa
spec:
scaleTargetRef:
apiVersion: extensions/v1beta1
kind: Deployment
name: nginx
minReplicas: 1
maxReplicas: 5
targetCPUUtilizationPercentage: 70
[root@master ~]#
这里只针对CPU的HPA 压力测试。
压测命令
[root@node1 ~]# cat test.sh while true do wget -q -O- http://192.168.1.204:30080 done [root@node1 ~]# sh test.sh
观察HPA当前负载和POD的情况
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 0% / 70% 1 5 1 14h [root@master ~]#
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 14% / 70% 1 5 1 14h [root@master ~]#
当负载飙升时，HPA会按照定义的规则开始创建新的POD副本(定义POD的CPU阈值为70%)。
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 180% / 70% 1 5 3 14h [root@master ~]# [root@master ~]# kubectl get pod -o wide NAME READY STATUS RESTARTS AGE IP NODE nginx-5dcf548595-bk9cr 1/1 Running 1 15h 172.30.94.2 192.168.1.205 nginx-5dcf548595-pdndb 1/1 Running 0 1m 172.30.94.4 192.168.1.205 nginx-5dcf548595-z9d6h 1/1 Running 0 1m 172.30.94.3 192.168.1.205 [root@master ~]#
继续压测，会发现POD副本数量继续增加（REPLICAS从3到5）。
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 139% / 70% 1 5 5 14h [root@master ~]# [root@master ~]# kubectl get pod -o wide NAME READY STATUS RESTARTS AGE IP NODE nginx-5dcf548595-9gmqf 0/1 ContainerCreating 0 39s <none> 192.168.1.204 nginx-5dcf548595-bk9cr 1/1 Running 1 15h 172.30.94.2 192.168.1.205 nginx-5dcf548595-pdndb 1/1 Running 0 10m 172.30.94.4 192.168.1.205 nginx-5dcf548595-r7n4b 1/1 Running 0 39s 172.30.94.5 192.168.1.205 nginx-5dcf548595-z9d6h 1/1 Running 0 10m 172.30.94.3 192.168.1.205 [root@master ~]#
当REPLICAS达到定义的上限时，即使当前CPU的压力仍然很大，REPLICAS也不会再增加了。
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 112% / 70% 1 5 5 14h [root@master ~]# [root@master ~]# kubectl get pod -o wide NAME READY STATUS RESTARTS AGE IP NODE nginx-5dcf548595-9gmqf 1/1 Running 0 2m 172.30.9.6 192.168.1.204 nginx-5dcf548595-bk9cr 1/1 Running 1 15h 172.30.94.2 192.168.1.205 nginx-5dcf548595-pdndb 1/1 Running 0 12m 172.30.94.4 192.168.1.205 nginx-5dcf548595-r7n4b 1/1 Running 0 2m 172.30.94.5 192.168.1.205 nginx-5dcf548595-z9d6h 1/1 Running 0 12m 172.30.94.3 192.168.1.205 [root@master ~]#
停止压测，当CPU负载降低时，HPA会自动减少POD的数量。
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 40% / 70% 1 5 3 14h [root@master ~]# [root@master ~]# kubectl get pod -o wide NAME READY STATUS RESTARTS AGE IP NODE nginx-5dcf548595-pdndb 1/1 Running 0 16m 172.30.94.4 192.168.1.205 nginx-5dcf548595-r7n4b 1/1 Running 0 6m 172.30.94.5 192.168.1.205 nginx-5dcf548595-z9d6h 1/1 Running 0 16m 172.30.94.3 192.168.1.205 [root@master ~]#
慢慢的，HPA会减少POD的数量，直到降低到最小POD数(MINPODS)。
[root@master ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 0% / 70% 1 5 1 15h [root@master ~]# [root@master ~]# kubectl get pod -o wide NAME READY STATUS RESTARTS AGE IP NODE nginx-5dcf548595-z9d6h 1/1 Running 0 1h 172.30.94.3 192.168.1.205 [root@master ~]#
通过kube-dashboard观察这个过程的变化。
通过HPA的日志信息查看到它伸缩的过程。
[root@master ~]# kubectl describe hpa
Name: nginx-hpa
Namespace: default
Labels: <none>
Annotations: kubectl.kubernetes.io/last-applied-configuration={"apiVersion":"au
toscaling/v1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"nginx-hpa","namespace":"default"},"spec":{"maxRepl...CreationTimestamp: Sun, 27 Jan 2019 01:04:25 +0800
Reference: Deployment/nginx
Metrics: ( current / target )
resource cpu on pods (as a percentage of request): 0% (0) / 70%
Min replicas: 1
Max replicas: 5
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale False BackoffDownscale the time since the previous scale is still within the downscale forbidden window
ScalingActive True ValidMetricFound the HPA was able to succesfully 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:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal SuccessfulRescale 41m (x2 over 1h) horizontal-pod-autoscaler New size: 5; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 29m (x2 over 1h) horizontal-pod-autoscaler New size: 3; reason: All metrics below target
Normal SuccessfulRescale 17m horizontal-pod-autoscaler New size: 2; reason: All metrics below target
Normal SuccessfulRescale 8m (x2 over 1h) horizontal-pod-autoscaler New size: 3; reason: cpu resource utilization (percentage of request) above target
Normal SuccessfulRescale 3m (x2 over 12m) horizontal-pod-autoscaler New size: 1; reason: All metrics below target
[root@master ~]#
autoscaling/v2beta1
autoscaling/v2beta1 中增加支持custom metrics。
[root@master ~]# cat nginx-hpa-v2beta1.yml
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: nginx-hpa
spec:
scaleTargetRef:
apiVersion: extensions/v1beta1
kind: Deployment
name: nginx
minReplicas: 1
maxReplicas: 5
metrics:
- type: Resource
resource:
name: memory
targetAverageUtilization: 70
- type: Resource
resource:
name: cpu
targetAverageUtilization: 70
[root@master ~]#
[root@master ~]# kubectl apply -f nginx-hpa-v2beta1.yml
等待几分钟后…
观察发现前面10%是内存的使用百分比，后面0%是CPU的使用百分比。
[root@master ~]# kubectl get hpa nginx-hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE nginx-hpa Deployment/nginx 10% / 70%, 0% / 70% 1 5 1 51s [root@master ~]#
[root@master ~]# kubectl describe hpa nginx-hpa
Name: nginx-hpa
Namespace: default
Labels: <none>
Annotations: kubectl.kubernetes.io/last-applied-configuration={"apiVersion":
"autoscaling/v2beta1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"nginx-hpa","namespace":"default"},"spec":{"ma...CreationTimestamp: Mon, 28 Jan 2019 22:22:01 +0800
Reference: Deployment/nginx
Metrics: ( current / target )
resource memory on pods (as a percentage of request): 10% (2670592) / 70%
resource cpu on pods (as a percentage of request): 0% (0) / 70%
Min replicas: 1
Max replicas: 5
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 succesfully calculate a replica count from memory resou
rce utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range
Events: <none>
[root@master ~]#
autoscaling/v2beta2
autoscaling/v2beta2 测试发现目前k8s 1.9.2暂不支持这个API版本。
[root@master ~]# kubectl get hpa.v2beta2.autoscaling -o yaml the server doesn't have a resource type "hpa" in group "v2beta2.autoscaling" [root@master ~]#
参考：
http://blog.51cto.com/ylw6006/2113848
https://blog.frognew.com/2017/01/kubernetes-pod-scale.html
https://k8smeetup.github.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/
https://blog.csdn.net/qq_17016649/article/details/79297796
https://github.com/kubernetes/kubernetes/issues/57673附件：
HPA测试配置文件.zip以上所述就是小编给大家介绍的《k8s集群水平扩展(HPA)》，希望对大家有所帮助，如果大家有任何疑问请给我留言，小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持！
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UML基础、案例与应用
施穆勒 / 李虎、赵龙刚 / 人民邮电出版社 / 2004-7-1 / 42.00元
本书教读者循序渐进地、系统地学习UML基础知识和应用技术。和前一版相比，本书内容根据UML 2.0进行了补充和更新，随书光盘包含了建模工具Poseidon的试用版。 全书分为三部分24章。第一部分“基础知识”包括第1章到第15章，主要是介绍UML语言的基础知识以及面向对象的概念和思想，还简单介绍了UML在开发过程的应用方法。第二部分“学习案例”包括第16章到第22章，结合实例详细分析了UML的应用......一起来看看 《UML基础、案例与应用》 这本书的介绍吧!
