VPA 全称 Vertical Pod Autoscaler,即垂直 Pod 自动扩缩容,它根据容器资源使用率自动设置 CPU 和 内存 的requests,从而允许在节点上进行适当的调度,以便为每个 Pod 提供适当的资源。
它既可以缩小过度请求资源的容器,也可以根据其使用情况随时提升资源不足的容量。
PS: VPA不会改变Pod的资源limits值。
废话不多说,直接上图,看VPA工作流程
接下来开始实战
部署metrics-server
1、下载部署清单文件
wget https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.7/components.yaml
2、修改components.yaml文件
- 修改了镜像地址,gcr.io为我自己的仓库
- 修改了metrics-server启动参数args,要不然会报错
unable to fully scrape metrics from source kubelet_summary...
- name: metrics-server
image: scofield/metrics-server:v0.3.7
imagePullPolicy: IfNotPresent
args:
- --cert-dir=/tmp
- --secure-port=4443
- /metrics-server
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP
3、执行部署
kubectl apply -f components.yaml
4、验证
[root@k8s-node001 metrics-server]# kubectl get po -n kube-system
NAME READY STATUS RESTARTS AGE
metrics-server-7947cb98b6-xw6b8 1/1 Running 0 10m
能获取要top信息视为成功
[root@k8s-node001 metrics-server]# kubectl top nodes
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
k8s-node001 618m 7% 4796Mi 15%
k8s-node003 551m 6% 5522Mi 17%
k8s-node004 308m 3% 5830Mi 18%
k8s-node005 526m 6% 5997Mi 38%
k8s-node002 591m 7% 5306Mi 33%
部署vertical-pod-autoscaler
1、克隆autoscaler项目
git clone https://github.com/kubernetes/autoscaler.git
2、修改部署文件,将gcr仓库该为我自己的仓库
admission-controller-deployment.yaml
us.gcr.io/k8s-artifacts-prod/autoscaling/vpa-admission-controller:0.8.0
改为
scofield/vpa-admission-controller:0.8.0
recommender-deployment.yaml
us.gcr.io/k8s-artifacts-prod/autoscaling/vpa-recommender:0.8.0
改为
image: scofield/vpa-recommender:0.8.0
updater-deployment.yaml
us.gcr.io/k8s-artifacts-prod/autoscaling/vpa-updater:0.8.0
改为
scofield/vpa-updater:0.8.0
3、部署
[root@k8s-node001 vertical-pod-autoscaler]# cd autoscaler/vertical-pod-autoscaler
[root@k8s-node001 vertical-pod-autoscaler]# ./hack/vpa-up.sh
Warning: apiextensions.k8s.io/v1beta1 CustomResourceDefinition is deprecated in v1.16+, unavailable in v1.22+; use apiextensions.k8s.io/v1 CustomResourceDefinition
customresourcedefinition.apiextensions.k8s.io/verticalpodautoscalers.autoscaling.k8s.io created
customresourcedefinition.apiextensions.k8s.io/verticalpodautoscalercheckpoints.autoscaling.k8s.io created
clusterrole.rbac.authorization.k8s.io/system:metrics-reader created
clusterrole.rbac.authorization.k8s.io/system:vpa-actor created
clusterrole.rbac.authorization.k8s.io/system:vpa-checkpoint-actor created
clusterrole.rbac.authorization.k8s.io/system:evictioner created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-reader created
clusterrolebinding.rbac.authorization.k8s.io/system:vpa-actor created
clusterrolebinding.rbac.authorization.k8s.io/system:vpa-checkpoint-actor created
clusterrole.rbac.authorization.k8s.io/system:vpa-target-reader created
clusterrolebinding.rbac.authorization.k8s.io/system:vpa-target-reader-binding created
clusterrolebinding.rbac.authorization.k8s.io/system:vpa-evictionter-binding created
serviceaccount/vpa-admission-controller created
clusterrole.rbac.authorization.k8s.io/system:vpa-admission-controller created
clusterrolebinding.rbac.authorization.k8s.io/system:vpa-admission-controller created
clusterrole.rbac.authorization.k8s.io/system:vpa-status-reader created
clusterrolebinding.rbac.authorization.k8s.io/system:vpa-status-reader-binding created
serviceaccount/vpa-updater created
deployment.apps/vpa-updater created
serviceaccount/vpa-recommender created
deployment.apps/vpa-recommender created
Generating certs for the VPA Admission Controller in /tmp/vpa-certs.
Generating RSA private key, 2048 bit long modulus (2 primes)
............................................................................+++++
.+++++
e is 65537 (0x010001)
Generating RSA private key, 2048 bit long modulus (2 primes)
............+++++
...........................................................................+++++
e is 65537 (0x010001)
Signature ok
subject=CN = vpa-webhook.kube-system.svc
Getting CA Private Key
Uploading certs to the cluster.
secret/vpa-tls-certs created
Deleting /tmp/vpa-certs.
deployment.apps/vpa-admission-controller created
service/vpa-webhook created
4、查看结果,可以看到metrics-server和vpa都已经正常运行了
[root@k8s-node001 autoscaler-master]# kubectl get po -n kube-system
NAME READY STATUS RESTARTS AGE
metrics-server-7947cb98b6-xw6b8 1/1 Running 0 46m
vpa-admission-controller-7d87559549-g77h9 1/1 Running 0 10m
vpa-recommender-84bf7fb9db-65669 1/1 Running 0 10m
vpa-updater-79cc46c7bb-5p889 1/1 Running 0 10m
示例1 updateMode: "Off"
1、首先我们部署一个nginx服务,部署到namespace: vpa中
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: nginx
name: nginx
namespace: vpa
spec:
replicas: 2
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- image: nginx
name: nginx
resources:
requests:
cpu: 100m
memory: 250Mi
看下结果,正常运行了2个pod
[root@k8s-node001 examples]# kubectl get po -n vpa
NAME READY STATUS RESTARTS AGE
pod/nginx-6884b849f7-fswx5 1/1 Running 0 5m54s
pod/nginx-6884b849f7-wz6b8 1/1 Running 0 5m54s
2、为了便宜压测,我们创建一个NodePort类型的service
[root@k8s-node001 examples]# cat nginx-vpa-ingress.yaml
apiVersion: v1
kind: Service
metadata:
name: nginx
namespace: vpa
spec:
type: NodePort
ports:
- port: 80
targetPort: 80
selector:
app: nginx
[root@k8s-node001 examples]# kubectl get svc -n vpa
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
nginx NodePort 10.97.250.131 <none> 80:32621/TCP 55s
[root@k8s-node001 examples]# curl -I 192.168.100.185:32621
HTTP/1.1 200 OK
3、创建VPA
这里先使用updateMode: "Off"模式,这种模式仅获取资源推荐不更新Pod
[root@k8s-node001 examples]# cat nginx-vpa-demo.yaml
apiVersion: autoscaling.k8s.io/v1beta2
kind: VerticalPodAutoscaler
metadata:
name: nginx-vpa
namespace: vpa
spec:
targetRef:
apiVersion: "apps/v1"
kind: Deployment
name: nginx
updatePolicy:
updateMode: "Off"
resourcePolicy:
containerPolicies:
- containerName: "nginx"
minAllowed:
cpu: "250m"
memory: "100Mi"
maxAllowed:
cpu: "2000m"
memory: "2048Mi"
4、查看部署结果
[root@k8s-node001 examples]# kubectl get vpa -n vpa
NAME AGE
nginx-vpa 2m34s
5、使用describe查看vpa详情,主要关注Container Recommendations
[root@k8s-node001 examples]# kubectl describe vpa nginx-vpa -n vpa
Name: nginx-vpa
Namespace: vpa
....略去10000字 哈哈......
Update Policy:
Update Mode: Off
Status:
Conditions:
Last Transition Time: 2020-09-28T04:04:25Z
Status: True
Type: RecommendationProvided
Recommendation:
Container Recommendations:
Container Name: nginx
Lower Bound:
Cpu: 250m
Memory: 262144k
Target:
Cpu: 250m
Memory: 262144k
Uncapped Target:
Cpu: 25m
Memory: 262144k
Upper Bound:
Cpu: 803m
Memory: 840190575
Events: <none>
其中
Lower Bound: 下限值
Target: 推荐值
Upper Bound: 上限值
Uncapped Target: 如果没有为VPA提供最小或最大边界,则表示目标利用率
上述结果表明,推荐的 Pod 的 CPU 请求为 25m,推荐的内存请求为 262144k 字节。
6、现在我们对nginx进行压测
执行压测命令
[root@k8s-node001 examples]# ab -c 100 -n 10000000 http://192.168.100.185:32621/
This is ApacheBench, Version 2.3 <$Revision: 1843412 $>
Copyright 1996 Adam Twiss, Zeus Technology Ltd, http://www.zeustech.net/
Licensed to The Apache Software Foundation, http://www.apache.org/
Benchmarking 192.168.100.185 (be patient)
Completed 1000000 requests
Completed 2000000 requests
Completed 3000000 requests
7、几分钟后再观察VPA Recommendation变化
[root@k8s-node001 ~]# kubectl describe vpa nginx-vpa -n vpa |tail -n 20
Conditions:
Last Transition Time: 2020-09-28T04:04:25Z
Status: True
Type: RecommendationProvided
Recommendation:
Container Recommendations:
Container Name: nginx
Lower Bound:
Cpu: 250m
Memory: 262144k
Target:
Cpu: 476m
Memory: 262144k
Uncapped Target:
Cpu: 476m
Memory: 262144k
Upper Bound:
Cpu: 2
Memory: 387578728
Events: <none>
从输出信息可以看出,VPA对Pod给出了推荐值:Cpu: 476m
,因为我们这里设置了updateMode: "Off",所以不会更新Pod
示例2 updateMode: "Auto"
1、现在我把updateMode: "Auto",看看VPA会有什么动作
这里我把resources改为:memory: 50Mi,cpu: 100m
[root@k8s-node001 examples]# kubectl apply -f nginx-vpa.yaml
deployment.apps/nginx created
[root@k8s-node001 examples]# cat nginx-vpa.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: nginx
name: nginx
namespace: vpa
spec:
replicas: 2
selector:
matchLabels:
app: nginx
template:
metadata:
labels:
app: nginx
spec:
containers:
- image: nginx
name: nginx
resources:
requests:
cpu: 100m
memory: 50Mi
[root@k8s-node001 examples]# kubectl get po -n vpa
NAME READY STATUS RESTARTS AGE
nginx-7ff65f974c-f4vgl 1/1 Running 0 114s
nginx-7ff65f974c-v9ccx 1/1 Running 0 114s
2、再次部署vpa,这里VPA部署文件nginx-vpa-demo.yaml只改了updateMode: "Auto"
和name: nginx-vpa-2
[root@k8s-node001 examples]# cat nginx-vpa-demo.yaml
apiVersion: autoscaling.k8s.io/v1beta2
kind: VerticalPodAutoscaler
metadata:
name: nginx-vpa-2
namespace: vpa
spec:
targetRef:
apiVersion: "apps/v1"
kind: Deployment
name: nginx
updatePolicy:
updateMode: "Auto"
resourcePolicy:
containerPolicies:
- containerName: "nginx"
minAllowed:
cpu: "250m"
memory: "100Mi"
maxAllowed:
cpu: "2000m"
memory: "2048Mi"
[root@k8s-node001 examples]# kubectl apply -f nginx-vpa-demo.yaml
verticalpodautoscaler.autoscaling.k8s.io/nginx-vpa created
[root@k8s-node001 examples]# kubectl get vpa -n vpa
NAME AGE
nginx-vpa-2 9s
3、再次压测
ab -c 1000 -n 100000000 http://192.168.100.185:32621/
4、几分钟后,使用describe查看vpa详情,同样只关注Container Recommendations
[root@k8s-node001 ~]# kubectl describe vpa nginx-vpa-2 -n vpa |tail -n 30
Min Allowed:
Cpu: 250m
Memory: 100Mi
Target Ref:
API Version: apps/v1
Kind: Deployment
Name: nginx
Update Policy:
Update Mode: Auto
Status:
Conditions:
Last Transition Time: 2020-09-28T04:48:25Z
Status: True
Type: RecommendationProvided
Recommendation:
Container Recommendations:
Container Name: nginx
Lower Bound:
Cpu: 250m
Memory: 262144k
Target:
Cpu: 476m
Memory: 262144k
Uncapped Target:
Cpu: 476m
Memory: 262144k
Upper Bound:
Cpu: 2
Memory: 262144k
Events: <none>
Target变成了Cpu: 587m ,Memory: 262144k
5、来看下event事件
[root@k8s-node001 ~]# kubectl get event -n vpa
LAST SEEN TYPE REASON OBJECT MESSAGE
33m Normal Pulling pod/nginx-7ff65f974c-f4vgl Pulling image "nginx"
33m Normal Pulled pod/nginx-7ff65f974c-f4vgl Successfully pulled image "nginx" in 15.880996269s
33m Normal Created pod/nginx-7ff65f974c-f4vgl Created container nginx
33m Normal Started pod/nginx-7ff65f974c-f4vgl Started container nginx
26m Normal EvictedByVPA pod/nginx-7ff65f974c-f4vgl Pod was evicted by VPA Updater to apply resource recommendation.
26m Normal Killing pod/nginx-7ff65f974c-f4vgl Stopping container nginx
35m Normal Scheduled pod/nginx-7ff65f974c-hnzr5 Successfully assigned vpa/nginx-7ff65f974c-hnzr5 to k8s-node005
35m Normal Pulling pod/nginx-7ff65f974c-hnzr5 Pulling image "nginx"
34m Normal Pulled pod/nginx-7ff65f974c-hnzr5 Successfully pulled image "nginx" in 40.750855715s
34m Normal Scheduled pod/nginx-7ff65f974c-v9ccx Successfully assigned vpa/nginx-7ff65f974c-v9ccx to k8s-node004
33m Normal Pulling pod/nginx-7ff65f974c-v9ccx Pulling image "nginx"
33m Normal Pulled pod/nginx-7ff65f974c-v9ccx Successfully pulled image "nginx" in 15.495315629s
33m Normal Created pod/nginx-7ff65f974c-v9ccx Created container nginx
33m Normal Started pod/nginx-7ff65f974c-v9ccx Started container nginx
从输出信息可以了解到,vpa执行了EvictedByVPA,自动停掉了nginx,然后使用 VPA推荐的资源启动了新的nginx
,我们查看下nginx的pod可以得到确认
[root@k8s-node001 ~]# kubectl describe po nginx-7ff65f974c-2m9zl -n vpa
Name: nginx-7ff65f974c-2m9zl
Namespace: vpa
Priority: 0
Node: k8s-node004/192.168.100.184
Start Time: Mon, 28 Sep 2020 00:46:19 -0400
Labels: app=nginx
pod-template-hash=7ff65f974c
Annotations: cni.projectcalico.org/podIP: 100.67.191.53/32
vpaObservedContainers: nginx
vpaUpdates: Pod resources updated by nginx-vpa: container 0: cpu request, memory request
Status: Running
IP: 100.67.191.53
IPs:
IP: 100.67.191.53
Controlled By: ReplicaSet/nginx-7ff65f974c
Containers:
nginx:
Container ID: docker://c96bcd07f35409d47232a0bf862a76a56352bd84ef10a95de8b2e3f6681df43d
Image: nginx
Image ID: docker-pullable://nginx@sha256:c628b67d21744fce822d22fdcc0389f6bd763daac23a6b77147d0712ea7102d0
Port: <none>
Host Port: <none>
State: Running
Started: Mon, 28 Sep 2020 00:46:38 -0400
Ready: True
Restart Count: 0
Requests:
cpu: 476m
memory: 262144k
看重点Requests:cpu: 476m,memory: 262144k
再回头看看部署文件
requests:
cpu: 100m
memory: 50Mi
现在可以知道VPA做了哪些事了吧。当然,随着服务的负载的变化,VPA的推荐之也会不断变化。当目前运行的pod的资源达不到VPA的推荐值,就会执行pod驱逐,重新部署新的足够资源的服务。
VPA使用限制
- 不能与HPA(Horizontal Pod Autoscaler )一起使用
- Pod比如使用副本控制器,例如属于Deployment或者StatefulSet
VPA有啥好处
- Pod 资源用其所需,所以集群节点使用效率高。
- Pod 会被安排到具有适当可用资源的节点上。
- 不必运行基准测试任务来确定 CPU 和内存请求的合适值。
- VPA 可以随时调整 CPU 和内存请求,无需人为操作,因此可以减少维护时间。
最后滴最后,VPA是Kubernetes比较新的功能,还没有在生产环境大规模实践过,不建议在线上环境使用自动更新模式,但是使用推荐模式你可以更好了解服务的资源使用情况。
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