当前位置 博文首页 > Linux-1874：容器编排系统K8s之HPA资源
前文我们了解了用Prometheus监控k8s上的节点和pod资源，回顾请参考：https://www.cnblogs.com/qiuhom-1874/p/14287942.html；今天我们来了解下k8s上的HPA资源的使用；
HPA的全称是Horizontal Pod Autoscaler，从字面意思理解它就是水平pod自动伸缩器；简单讲HPA的主要作用是根据指定的指标数据，监控对应的pod控制器，一旦对应pod控制器下的pod的对应指标数据达到我们定义的阀值，即HPA就会被触发，它会根据对应指标数据的值来扩展/缩减对应pod副本数量；扩展和缩减都是有上下限的，当pod数量达到上限，即便指标数据还是超过了我们定义的阀值它也不会再扩展，对于下线默认不指定就是为1；下限和上限都是一样的逻辑，即便一个访问都没有，它会保持最低有多少个pod运行；需注意hpa只能用于监控可扩缩的pod控制器，对DaemonSet类型控制器不支持；
在k8s上HPA有两个版本v1和v2；v1只支持根据cpu这个指标数据来自动扩展/缩减pod数量；V2支持根据自定义指标数量来自动扩展/缩减pod数量；HPA是k8s上的标准资源，我们可以通过命令或资源清单的方式去创建它；
使用命令创建HPA资源的使用语法格式
Usage: kubectl autoscale (-f FILENAME | TYPE NAME | TYPE/NAME) [--min=MINPODS] --max=MAXPODS [--cpu-percent=CPU] [options]
提示：默认不指定hpa的名称，它会同对应的pod控制名称相同；--min选项用于指定对应pod副本最低数量，默认不指定其值为1，--max用于指定pod最大副本数量；--cpu-percent选项用于指定对应pod的cpu资源的占用比例，该占用比例是同对应pod的资源限制做比较；
示例：使用命令创建v1版本的hpa资源
使用deploy控制器创建pod资源
HPA的全称是Horizontal Pod Autoscaler，从字面意思理解它就是水平pod自动伸缩器；简单讲HPA的主要作用是根据指定的指标数据，监控对应的pod控制器，一旦对应pod控制器下的pod的对应指标数据达到我们定义的阀值，即HPA就会被触发，它会根据对应指标数据的值来扩展/缩减对应pod副本数量；扩展和缩减都是有上下限的，当pod数量达到上限，即便指标数据还是超过了我们定义的阀值它也不会再扩展，对于下线默认不指定就是为1；下限和上限都是一样的逻辑，即便一个访问都没有，它会保持最低有多少个pod运行；需注意hpa只能用于监控可扩缩的pod控制器，对DaemonSet类型控制器不支持；
[root@master01 ~]# cat myapp.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: myapp
namespace: default
labels:
app: myapp
spec:
replicas: 2
selector:
matchLabels:
app: myapp
template:
metadata:
name: myapp-pod
labels:
app: myapp
spec:
containers:
- name: myapp
image: ikubernetes/myapp:v1
resources:
requests:
cpu: 50m
memory: 64Mi
limits:
cpu: 50m
memory: 64Mi
---
apiVersion: v1
kind: Service
metadata:
name: myapp-svc
labels:
app: myapp
namespace: default
spec:
selector:
app: myapp
ports:
- name: http
port: 80
targetPort: 80
type: NodePort
[root@master01 ~]#
应用资源清单
[root@master01 ~]# kubectl apply -f myapp.yaml deployment.apps/myapp created service/myapp-svc created [root@master01 ~]# kubectl get pods NAME READY STATUS RESTARTS AGE myapp-779867bcfc-657qr 1/1 Running 0 6s myapp-779867bcfc-txvj8 1/1 Running 0 6s [root@master01 ~]# kubectl get svc NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 8d myapp-svc NodePort 10.111.14.219 <none> 80:31154/TCP 13s [root@master01 ~]#
查看pod的资源占比情况
[root@master01 ~]# kubectl top pods NAME CPU(cores) MEMORY(bytes) myapp-779867bcfc-657qr 0m 3Mi myapp-779867bcfc-txvj8 0m 3Mi [root@master01 ~]#
提示：现在没有访问对应pod，其cpu指标为0；
使用命令创建hpa资源，监控myapp deploy，指定对应pod的cpu资源使用率达到50%就触发hpa
[root@master01 ~]# kubectl autoscale deploy myapp --min=2 --max=10 --cpu-percent=50 horizontalpodautoscaler.autoscaling/myapp autoscaled [root@master01 ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE myapp Deployment/myapp <unknown>/50% 2 10 0 10s [root@master01 ~]# kubectl describe hpa/myapp Name: myapp Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Mon, 18 Jan 2021 15:26:49 +0800 Reference: Deployment/myapp Metrics: ( current / target ) resource cpu on pods (as a percentage of request): 0% (0) / 50% Min replicas: 2 Max replicas: 10 Deployment pods: 2 current / 2 desired Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True ScaleDownStabilized recent recommendations were higher than current one, applying the highest recent recommendation ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: <none> [root@master01 ~]#
验证：使用ab压测工具，对pod进行压力访问，看看对应pod cpu资源使用率大于50%，对应pod是否会扩展？
安装ab工具
yum install httpd-tools -y
使用外部主机对pod svc 进行压力访问
查看pod的资源占比情况
[root@master01 ~]# kubectl top pods NAME CPU(cores) MEMORY(bytes) myapp-779867bcfc-657qr 51m 4Mi myapp-779867bcfc-txvj8 34m 4Mi [root@master01 ~]#
提示：可以看到对应pod的cpu资源都大于限制的资源上限的50%；这里需要注意hpa扩展pod它有一定的延迟，不是立刻马上就扩展；
查看对应hpa资源的详情
提示：hpa详情告诉我们对应pod扩展到7个；
查看pod数量是否被扩展到7个？
[root@master01 ~]# kubectl get pods NAME READY STATUS RESTARTS AGE myapp-779867bcfc-657qr 1/1 Running 0 16m myapp-779867bcfc-7c4dt 1/1 Running 0 3m27s myapp-779867bcfc-b2jmn 1/1 Running 0 3m27s myapp-779867bcfc-fmw7v 1/1 Running 0 2m25s myapp-779867bcfc-hxhj2 1/1 Running 0 2m25s myapp-779867bcfc-txvj8 1/1 Running 0 16m myapp-779867bcfc-xvh58 1/1 Running 0 2m25s [root@master01 ~]#
提示：可以看到对应pod被控制到7个；
查看对应pod的资源占比是否还高于限制的50%？
[root@master01 ~]# kubectl top pods NAME CPU(cores) MEMORY(bytes) myapp-779867bcfc-657qr 49m 4Mi myapp-779867bcfc-7c4dt 25m 4Mi myapp-779867bcfc-b2jmn 36m 4Mi myapp-779867bcfc-fmw7v 42m 4Mi myapp-779867bcfc-hxhj2 46m 3Mi myapp-779867bcfc-txvj8 21m 4Mi myapp-779867bcfc-xvh58 49m 4Mi [root@master01 ~]#
提示：可以看到对应pod的cpu使用率还是高于限制的50%，说明扩展到pod数量不能够响应对应的请求，此时hpa还会扩展；
查看hpa详情，看看是否又一次扩展pod的数量？
提示：可以看到对应pod被扩展到10个，但是对应cpu资源使用率为94%，此时pod数量已经到达上限，即便对应指标数据还是大于指定的阀值，它也不会扩展；
查看pod数量是否为10个？
[root@master01 ~]# kubectl get pods NAME READY STATUS RESTARTS AGE myapp-779867bcfc-57zw7 1/1 Running 0 5m39s myapp-779867bcfc-657qr 1/1 Running 0 23m myapp-779867bcfc-7c4dt 1/1 Running 0 10m myapp-779867bcfc-b2jmn 1/1 Running 0 10m myapp-779867bcfc-dvq6k 1/1 Running 0 5m39s myapp-779867bcfc-fmw7v 1/1 Running 0 9m45s myapp-779867bcfc-hxhj2 1/1 Running 0 9m45s myapp-779867bcfc-n8lmf 1/1 Running 0 5m39s myapp-779867bcfc-txvj8 1/1 Running 0 23m myapp-779867bcfc-xvh58 1/1 Running 0 9m45s [root@master01 ~]#
停止压测，看看对应pod是否会缩减到最低pod数量为2个呢？
[root@master01 ~]# kubectl get pods NAME READY STATUS RESTARTS AGE myapp-779867bcfc-57zw7 1/1 Running 0 8m8s myapp-779867bcfc-657qr 1/1 Running 0 26m myapp-779867bcfc-7c4dt 1/1 Running 0 13m myapp-779867bcfc-b2jmn 1/1 Running 0 13m myapp-779867bcfc-dvq6k 1/1 Running 0 8m8s myapp-779867bcfc-fmw7v 1/1 Running 0 12m myapp-779867bcfc-hxhj2 1/1 Running 0 12m myapp-779867bcfc-n8lmf 1/1 Running 0 8m8s myapp-779867bcfc-txvj8 1/1 Running 0 26m myapp-779867bcfc-xvh58 1/1 Running 0 12m [root@master01 ~]# kubectl top pods NAME CPU(cores) MEMORY(bytes) myapp-779867bcfc-57zw7 0m 4Mi myapp-779867bcfc-657qr 0m 4Mi myapp-779867bcfc-7c4dt 7m 4Mi myapp-779867bcfc-b2jmn 0m 4Mi myapp-779867bcfc-dvq6k 0m 4Mi myapp-779867bcfc-fmw7v 0m 4Mi myapp-779867bcfc-hxhj2 3m 3Mi myapp-779867bcfc-n8lmf 10m 4Mi myapp-779867bcfc-txvj8 0m 4Mi myapp-779867bcfc-xvh58 0m 4Mi [root@master01 ~]#
提示：pod缩减也是不会立刻执行；从上面信息可以看到停止压测对应pod的cpu资源使用率都降下来了；
再次查看对应pod数量
[root@master01 ~]# kubectl top pods NAME CPU(cores) MEMORY(bytes) myapp-779867bcfc-57zw7 0m 4Mi myapp-779867bcfc-657qr 0m 4Mi [root@master01 ~]# kubectl get pods NAME READY STATUS RESTARTS AGE myapp-779867bcfc-57zw7 1/1 Running 0 13m myapp-779867bcfc-657qr 1/1 Running 0 31m [root@master01 ~]#
提示：可以看到对应pod缩减到最低pod副本数量；
查看hpa的详情
提示：可以看到对应pod的cpu使用率小于50%，它会隔一段时间就缩减对应pod；
示例：使用资源清单定义hpa资源
[root@master01 ~]# cat hpa-demo.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
name: hpa-demo
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: myapp
minReplicas: 2
maxReplicas: 10
targetCPUUtilizationPercentage: 50
[root@master01 ~]#
提示：以上是hpa v1的资源清单定义示例，其中targetCPUUtilizationPercentage用于指定cpu资源使用率阀值，50表示50%，即达到pod上限的50%对应hpa就会被触发；
应用清单
[root@master01 ~]# kubectl apply -f hpa-demo.yaml horizontalpodautoscaler.autoscaling/hpa-demo created [root@master01 ~]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE hpa-demo Deployment/myapp <unknown>/50% 2 10 0 8s myapp Deployment/myapp 0%/50% 2 10 2 35m [root@master01 ~]# kubectl describe hpa/hpa-demo Name: hpa-demo Namespace: default Labels: <none> Annotations: <none> CreationTimestamp: Mon, 18 Jan 2021 16:02:25 +0800 Reference: Deployment/myapp Metrics: ( current / target ) resource cpu on pods (as a percentage of request): 0% (0) / 50% Min replicas: 2 Max replicas: 10 Deployment pods: 2 current / 2 desired Conditions: Type Status Reason Message ---- ------ ------ ------- AbleToScale True ScaleDownStabilized recent recommendations were higher than current one, applying the highest recent recommendation ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from cpu resource utilization (percentage of request) ScalingLimited False DesiredWithinRange the desired count is within the acceptable range Events: <none> [root@master01 ~]#
提示：可以看到使用命令创建hpa和使用资源清单创建hpa其创建出来的hpa都是一样的；以上是hpa v1的使用示例和相关说明；使用命令创建hpa，只能创建v1的hpa；v2必须使用资源清单，明确指定对应hpa的群组版本；
使用自定义资源指标定义hpa
部署自定义资源指标服务器
下载部署清单
[root@master01 ~]# mkdir custom-metrics-server [root@master01 ~]# cd custom-metrics-server [root@master01 custom-metrics-server]# git clone https://github.com/stefanprodan/k8s-prom-hpa Cloning into 'k8s-prom-hpa'... remote: Enumerating objects: 223, done. remote: Total 223 (delta 0), reused 0 (delta 0), pack-reused 223 Receiving objects: 100% (223/223), 102.23 KiB | 14.00 KiB/s, done. Resolving deltas: 100% (117/117), done. [root@master01 custom-metrics-server]# ls k8s-prom-hpa [root@master01 custom-metrics-server]#
查看custom-metrics-server的部署清单
[root@master01 custom-metrics-server]# cd k8s-prom-hpa/
[root@master01 k8s-prom-hpa]# ls
custom-metrics-api diagrams ingress LICENSE Makefile metrics-server namespaces.yaml podinfo prometheus README.md
[root@master01 k8s-prom-hpa]# cd custom-metrics-api/
[root@master01 custom-metrics-api]# ls
custom-metrics-apiserver-auth-delegator-cluster-role-binding.yaml custom-metrics-apiservice.yaml
custom-metrics-apiserver-auth-reader-role-binding.yaml custom-metrics-cluster-role.yaml
custom-metrics-apiserver-deployment.yaml custom-metrics-config-map.yaml
custom-metrics-apiserver-resource-reader-cluster-role-binding.yaml custom-metrics-resource-reader-cluster-role.yaml
custom-metrics-apiserver-service-account.yaml hpa-custom-metrics-cluster-role-binding.yaml
custom-metrics-apiserver-service.yaml
[root@master01 custom-metrics-api]# cat custom-metrics-apiserver-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: custom-metrics-apiserver
name: custom-metrics-apiserver
namespace: monitoring
spec:
replicas: 1
selector:
matchLabels:
app: custom-metrics-apiserver
template:
metadata:
labels:
app: custom-metrics-apiserver
name: custom-metrics-apiserver
spec:
serviceAccountName: custom-metrics-apiserver
containers:
- name: custom-metrics-apiserver
image: quay.io/coreos/k8s-prometheus-adapter-amd64:v0.4.1
args:
- /adapter
- --secure-port=6443
- --tls-cert-file=/var/run/serving-cert/serving.crt
- --tls-private-key-file=/var/run/serving-cert/serving.key
- --logtostderr=true
- --prometheus-url=http://prometheus.monitoring.svc:9090/
- --metrics-relist-interval=30s
- --v=10
- --config=/etc/adapter/config.yaml
ports:
- containerPort: 6443
volumeMounts:
- mountPath: /var/run/serving-cert
name: volume-serving-cert
readOnly: true
- mountPath: /etc/adapter/
name: config
readOnly: true
volumes:
- name: volume-serving-cert
secret:
secretName: cm-adapter-serving-certs
- name: config
configMap:
name: adapter-config
[root@master01 custom-metrics-api]#
提示：上述清单中明确定义了把自定义指标服务器部署到monitoring名称空间下，对应server的启动还挂在了secret证书；所以应用上述清单前，我们要先创建名称空间和secret；在创建secret前还要先准备好证书和私钥；这里还需要注意custom-metrics-server是连接Prometheus server，把对应自定义数据通过apiservice注册到对应原生apiserver上，供k8s组件使用，所以这里要注意对应Prometheus的地址；
创建monitoring名称空间
[root@master01 custom-metrics-api]# cd .. [root@master01 k8s-prom-hpa]# ls custom-metrics-api diagrams ingress LICENSE Makefile metrics-server namespaces.yaml podinfo prometheus README.md [root@master01 k8s-prom-hpa]# cat namespaces.yaml --- apiVersion: v1 kind: Namespace metadata: name: monitoring [root@master01 k8s-prom-hpa]# kubectl apply -f namespaces.yaml namespace/monitoring created [root@master01 k8s-prom-hpa]# kubectl get ns NAME STATUS AGE default Active 41d ingress-nginx Active 27d kube-node-lease Active 41d kube-public Active 41d kube-system Active 41d kubernetes-dashboard Active 16d mongodb Active 4d20h monitoring Active 4s [root@master01 k8s-prom-hpa]#
生成serving.key和serving.csr
[root@master01 k8s-prom-hpa]# cd /etc/kubernetes/pki/ [root@master01 pki]# ls apiserver.crt apiserver.key ca.crt etcd front-proxy-client.crt sa.pub tom.key apiserver-etcd-client.crt apiserver-kubelet-client.crt ca.key front-proxy-ca.crt front-proxy-client.key tom.crt apiserver-etcd-client.key apiserver-kubelet-client.key ca.srl front-proxy-ca.key sa.key tom.csr [root@master01 pki]# openssl genrsa -out serving.key 2048 Generating RSA private key, 2048 bit long modulus .............................................................................................................................................................+++ ..............................+++ e is 65537 (0x10001) [root@master01 pki]# openssl req -new -key ./serving.key -out ./serving.csr -subj "/CN=serving" [root@master01 pki]# ll total 80 -rw-r--r-- 1 root root 1277 Dec 8 14:38 apiserver.crt -rw-r--r-- 1 root root 1135 Dec 8 14:38 apiserver-etcd-client.crt -rw------- 1 root root 1679 Dec 8 14:38 apiserver-etcd-client.key -rw------- 1 root root 1679 Dec 8 14:38 apiserver.key -rw-r--r-- 1 root root 1143 Dec 8 14:38 apiserver-kubelet-client.crt -rw------- 1 root root 1679 Dec 8 14:38 apiserver-kubelet-client.key -rw-r--r-- 1 root root 1066 Dec 8 14:38 ca.crt -rw------- 1 root root 1675 Dec 8 14:38 ca.key -rw-r--r-- 1 root root 17 Jan 17 13:03 ca.srl drwxr-xr-x 2 root root 162 Dec 8 14:38 etcd -rw-r--r-- 1 root root 1078 Dec 8 14:38 front-proxy-ca.crt -rw------- 1 root root 1675 Dec 8 14:38 front-proxy-ca.key -rw-r--r-- 1 root root 1103 Dec 8 14:38 front-proxy-client.crt -rw------- 1 root root 1679 Dec 8 14:38 front-proxy-client.key -rw------- 1 root root 1679 Dec 8 14:38 sa.key -rw------- 1 root root 451 Dec 8 14:38 sa.pub -rw-r--r-- 1 root root 887 Jan 18 16:54 serving.csr -rw-r--r-- 1 root root 1679 Jan 18 16:54 serving.key -rw-r--r-- 1 root root 993 Dec 30 00:29 tom.crt -rw-r--r-- 1 root root 907 Dec 30 00:27 tom.csr -rw-r--r-- 1 root root 1675 Dec 30 00:21 tom.key [root@master01 pki]#
用kubenetes CA的key和证书为custom-metrics-server签署证书
[root@master01 pki]# openssl x509 -req -in serving.csr -CA /etc/kubernetes/pki/ca.crt -CAkey /etc/kubernetes/pki/ca.key -CAcreateserial -out serving.crt -days 3650 Signature ok subject=/CN=serving Getting CA Private Key [root@master01 pki]# ll serving.crt -rw-r--r-- 1 root root 977 Jan 18 16:55 serving.crt [root@master01 pki]#
在monitoring名称空间下创建secret资源
[root@master01 pki]# kubectl create secret generic cm-adapter-serving-certs --from-file=./serving.key --from-file=./serving.crt -n monitoring secret/cm-adapter-serving-certs created [root@master01 pki]# kubectl get secret -n monitoring NAME TYPE DATA AGE cm-adapter-serving-certs Opaque 2 10s default-token-k64tz kubernetes.io/service-account-token 3 2m27s [root@master01 pki]# kubectl describe secret/cm-adapter-serving-certs -n monitoring Name: cm-adapter-serving-certs Namespace: monitoring Labels: <none> Annotations: <none> Type: Opaque Data ==== serving.crt: 977 bytes serving.key: 1679 bytes [root@master01 pki]#
提示：这里一定要使用generic类型创建secret，保持对应的名称为serving.key和serving.crt；创建secret的名称，必须同custom-metrics部署清单中的名称保持一致；
部署prometheus
[root@master01 pki]# cd /root/custom-metrics-server/k8s-prom-hpa/prometheus/
[root@master01 prometheus]# ls
prometheus-cfg.yaml prometheus-dep.yaml prometheus-rbac.yaml prometheus-svc.yaml
[root@master01 prometheus]# cat prometheus-dep.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus
namespace: monitoring
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
template:
metadata:
labels:
app: prometheus
annotations:
prometheus.io/scrape: 'false'
spec:
serviceAccountName: prometheus
containers:
- name: prometheus
image: prom/prometheus:v2.1.0
imagePullPolicy: Always
command:
- prometheus
- --config.file=/etc/prometheus/prometheus.yml
- --storage.tsdb.retention=1h
ports:
- containerPort: 9090
protocol: TCP
resources:
limits:
memory: 2Gi
volumeMounts:
- mountPath: /etc/prometheus/prometheus.yml
name: prometheus-config
subPath: prometheus.yml
volumes:
- name: prometheus-config
configMap:
name: prometheus-config
items:
- key: prometheus.yml
path: prometheus.yml
mode: 0644
[root@master01 prometheus]#
更改rbac资源清单中的群组版本为 rbac.authorization.k8s.io/v1
[root@master01 prometheus]# cat prometheus-rbac.yaml --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRole metadata: name: prometheus rules: - apiGroups: [""] resources: - nodes - nodes/proxy - services - endpoints - pods verbs: ["get", "list", "watch"] - apiGroups: - extensions resources: - ingresses verbs: ["get", "list", "watch"] - nonResourceURLs: ["/metrics"] verbs: ["get"] --- apiVersion: v1 kind: ServiceAccount metadata: name: prometheus namespace: monitoring --- apiVersion: rbac.authorization.k8s.io/v1 kind: ClusterRoleBinding metadata: name: prometheus roleRef: apiGroup: rbac.authorization.k8s.io kind: ClusterRole name: prometheus subjects: - kind: ServiceAccount name: prometheus namespace: monitoring [root@master01 prometheus]#
应用prometheus目录下的所有资源清单
[root@master01 prometheus]# kubectl apply -f . configmap/prometheus-config created deployment.apps/prometheus created clusterrole.rbac.authorization.k8s.io/prometheus created serviceaccount/prometheus created clusterrolebinding.rbac.authorization.k8s.io/prometheus created service/prometheus created [root@master01 prometheus]# kubectl get pods -n monitoring NAME READY STATUS RESTARTS AGE prometheus-5c5dc6d6d4-drrht 1/1 Running 0 26s [root@master01 prometheus]# kubectl get svc -n monitoring NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE prometheus NodePort 10.99.1.110 <none> 9090:31190/TCP 35s [root@master01 prometheus]#
部署自定义指标服务，应用custom-metrics-server目录下的所有资源清单
[root@master01 prometheus]# cd ../custom-metrics-api/ [root@master01 custom-metrics-api]# ls custom-metrics-apiserver-auth-delegator-cluster-role-binding.yaml custom-metrics-apiservice.yaml custom-metrics-apiserver-auth-reader-role-binding.yaml custom-metrics-cluster-role.yaml custom-metrics-apiserver-deployment.yaml custom-metrics-config-map.yaml custom-metrics-apiserver-resource-reader-cluster-role-binding.yaml custom-metrics-resource-reader-cluster-role.yaml custom-metrics-apiserver-service-account.yaml hpa-custom-metrics-cluster-role-binding.yaml custom-metrics-apiserver-service.yaml [root@master01 custom-metrics-api]# kubectl apply -f . clusterrolebinding.rbac.authorization.k8s.io/custom-metrics:system:auth-delegator created rolebinding.rbac.authorization.k8s.io/custom-metrics-auth-reader created deployment.apps/custom-metrics-apiserver created clusterrolebinding.rbac.authorization.k8s.io/custom-metrics-resource-reader created serviceaccount/custom-metrics-apiserver created service/custom-metrics-apiserver created apiservice.apiregistration.k8s.io/v1beta1.custom.metrics.k8s.io created clusterrole.rbac.authorization.k8s.io/custom-metrics-server-resources created configmap/adapter-config created clusterrole.rbac.authorization.k8s.io/custom-metrics-resource-reader created clusterrolebinding.rbac.authorization.k8s.io/hpa-controller-custom-metrics created [root@master01 custom-metrics-api]# kubectl get pods -n monitoring NAME READY STATUS RESTARTS AGE custom-metrics-apiserver-754dfc87c7-cdhqj 1/1 Running 0 18s prometheus-5c5dc6d6d4-drrht 1/1 Running 0 6m9s [root@master01 custom-metrics-api]# kubectl get svc -n monitoring NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE custom-metrics-apiserver ClusterIP 10.99.245.190 <none> 443/TCP 31s prometheus NodePort 10.99.1.110 <none> 9090:31190/TCP 6m21s [root@master01 custom-metrics-api]#
提示：应用上述清单前，请把所有rbac.authorization.k8s.io/v1beta1更改为rbac.authorization.k8s.io/v1，把apiservice中的版本为apiregistration.k8s.io/v1；如果是1.17之前的k8s，不用修改；
验证：查看原生apiserver是否有custom.metrics.k8s.io的群组注册进来？
[root@master01 custom-metrics-api]# kubectl api-versions|grep custom custom.metrics.k8s.io/v1beta1 [root@master01 custom-metrics-api]#
验证：访问对应群组，看看是否能够请求到自定义资源指标？
[root@master01 custom-metrics-api]# kubectl get --raw "/apis/metrics.k8s.io/v1beta1/" | jq .
{
"kind": "APIResourceList",
"apiVersion": "v1",
"groupVersion": "metrics.k8s.io/v1beta1",
"resources": [
{
"name": "nodes",
"singularName": "",
"namespaced": false,
"kind": "NodeMetrics",
"verbs": [
"get",
"list"
]
},
{
"name": "pods",
"singularName": "",
"namespaced": true,
"kind": "PodMetrics",
"verbs": [
"get",
"list"
]
}
]
}
[root@master01 custom-metrics-api]#
提示：如果访问对应群组能够响应数据，表示自定义资源指标服务器没有问题；
示例：创建podinfo pod，该pod输出http_requests资源指标
[root@master01 custom-metrics-api]# cd ..
[root@master01 k8s-prom-hpa]# ls
custom-metrics-api diagrams ingress LICENSE Makefile metrics-server namespaces.yaml podinfo prometheus README.md
[root@master01 k8s-prom-hpa]# cd podinfo/
[root@master01 podinfo]# ls
podinfo-dep.yaml podinfo-hpa-custom.yaml podinfo-hpa.yaml podinfo-ingress.yaml podinfo-svc.yaml
[root@master01 podinfo]# cat podinfo-dep.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: podinfo
spec:
selector:
matchLabels:
app: podinfo
replicas: 2
template:
metadata:
labels:
app: podinfo
annotations:
prometheus.io/scrape: "true"
spec:
containers:
- name: podinfod
image: stefanprodan/podinfo:0.0.1
imagePullPolicy: Always
command:
- ./podinfo
- -port=9898
- -logtostderr=true
- -v=2
volumeMounts:
- name: metadata
mountPath: /etc/podinfod/metadata
readOnly: true
ports:
- containerPort: 9898
protocol: TCP
readinessProbe:
httpGet:
path: /readyz
port: 9898
initialDelaySeconds: 1
periodSeconds: 2
failureThreshold: 1
livenessProbe:
httpGet:
path: /healthz
port: 9898
initialDelaySeconds: 1
periodSeconds: 3
failureThreshold: 2
resources:
requests:
memory: "32Mi"
cpu: "1m"
limits:
memory: "256Mi"
cpu: "100m"
volumes:
- name: metadata
downwardAPI:
items:
- path: "labels"
fieldRef:
fieldPath: metadata.labels
- path: "annotations"
fieldRef:
fieldPath: metadata.annotations
[root@master01 podinfo]# cat podinfo-svc.yaml
---
apiVersion: v1
kind: Service
metadata:
name: podinfo
labels:
app: podinfo
spec:
type: NodePort
ports:
- port: 9898
targetPort: 9898
nodePort: 31198
protocol: TCP
selector:
app: podinfo
[root@master01 podinfo]#
应用资源清单
[root@master01 podinfo]# kubectl apply -f podinfo-dep.yaml,./podinfo-svc.yaml deployment.apps/podinfo created service/podinfo created [root@master01 podinfo]# kubectl get svc NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 8d myapp-svc NodePort 10.111.14.219 <none> 80:31154/TCP 4h35m podinfo NodePort 10.111.10.211 <none> 9898:31198/TCP 17s [root@master01 podinfo]# kubectl get pods NAME READY STATUS RESTARTS AGE myapp-779867bcfc-57zw7 1/1 Running 0 4h18m myapp-779867bcfc-657qr 1/1 Running 0 4h36m podinfo-56874dc7f8-5rb9q 1/1 Running 0 40s podinfo-56874dc7f8-t6jgn 1/1 Running 0 40s [root@master01 podinfo]#
