kubernetes(31)：Prometheus-adapter+custom-metrics-api实现自定义HPA
prometheus-adapter+custom-metrics-api实现k8s自定义HPA
参考https://blog.51cto.com/juestnow/2413581
1 HPA简介
Horizontal Pod Autoscaling，简称HPA，是Kubernetes中实现POD水平自动伸缩的功能。为什么要水平而不叫垂直, 那是因为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
更多参考kubernetes(24)：基于metrics-server水平扩展-资源HPA
1.1 基于资源的HPA
参考 kubernetes(24)：基于metrics-server水平扩展-资源HPA
Metrics Server是一个集群范围的资源使用数据的聚合器，是Hepster的继承者。metrics server通过kubernetes.summary_api收集节点和pod的CPU和memory使用率，根据CPU和内存使用情况pod自动扩展。这种方式主要是资源层面的，根据资源计算。
1.2 自定义HPA（例如qps）
也可以通过prometheus和custom API server，向聚合器层注册自定义API服务，然后使用演示程序提供的自定义metrics配置HPA，例如基于http请求访问次数的HPA。
Metrics Server和custom-metrics-api都有多种部署方式，比较推荐
https://github.com/stefanprodan/k8s-prom-hpa
我们这里前面部署了PrometheusOperator，我们这里用它提供的custom-metrics-api。
2 部署准备
部署PrometheusOperator所有的容器组都运行在monitoring 命名空间
地址git clone https://github.com/coreos/kube-prometheus
Prometheus之前已经部署完成
否则请参考 Prometheus监控k8s(10)-PrometheusOperator-更优雅的Prometheus部署
3 部署custom-metrics-api
cd kube-prometheus/experimental/custom-metrics-api/ kubectl apply -f custom-metrics-apiserver-resource-reader-cluster-role-binding.yaml kubectl apply -f custom-metrics-apiservice.yaml kubectl apply -f custom-metrics-cluster-role.yaml kubectl apply -f custom-metrics-configmap.yaml kubectl apply -f hpa-custom-metrics-cluster-role-binding.yam
4 调整部署prometheus-adapter
prometheus的安装参考
Prometheus监控k8s(2)-手动部署Prometheus
或Prometheus监控k8s(10)-PrometheusOperator-更优雅的Prometheus部署
部署prometheus的时候adapter已经部署，这个修改一下
[root@k8s-master experimental]# kubectl get pods -n monitoring -o wide | grep prometheus-adapter prometheus-adapter-668748ddbd-9h8g4 1/1 Running 0 19h 10.254.1.247 k8s-node-1 <none> <none> [root@k8s-master experimental]#
4.1 整理prometheus-adapter yaml
[root@k8s-master kube-prometheus]# cd - /root/prometheus/kube-prometheus/experimental [root@k8s-master experimental]# cd ../manifests/ [root@k8s-master manifests]# mkdir prometheus-adapter [root@k8s-master manifests]# mv prometheus-adapter*.yaml prometheus-adapter [root@k8s-master manifests]# cd prometheus-adapter [root@k8s-master prometheus-adapter]# ls prometheus-adapter-apiService.yaml prometheus-adapter-configMap.yaml prometheus-adapter-clusterRoleAggregatedMetricsReader.yaml prometheus-adapter-deployment.yaml prometheus-adapter-clusterRoleBindingDelegator.yaml prometheus-adapter-roleBindingAuthReader.yaml prometheus-adapter-clusterRoleBinding.yaml prometheus-adapter-serviceAccount.yaml prometheus-adapter-clusterRoleServerResources.yaml prometheus-adapter-service.yaml prometheus-adapter-clusterRole.yaml [root@k8s-master prometheus-adapter]# [root@k8s-master prometheus-adapter]# kubectl delete -f . clusterrole.rbac.authorization.k8s.io "prometheus-adapter" deleted clusterrolebinding.rbac.authorization.k8s.io "prometheus-adapter" deleted clusterrolebinding.rbac.authorization.k8s.io "resource-metrics:system:auth-delegator" deleted clusterrole.rbac.authorization.k8s.io "resource-metrics-server-resources" deleted configmap "adapter-config" deleted deployment.apps "prometheus-adapter" deleted rolebinding.rbac.authorization.k8s.io "resource-metrics-auth-reader" deleted service "prometheus-adapter" deleted serviceaccount "prometheus-adapter" deleted [root@k8s-master prometheus-adapter]# mv prometheus-adapter-configMap.yaml /tmp/ [root@k8s-master prometheus-adapter]#
说明：custom-metrics-api里面已经有configmap不能覆盖，删除或者移走
4.2 生成由Prometheus adapter所需的TLS证书
### 创建secret
kubectl create secret generic volume-serving-cert --from-file=apiserver.crt --from-file=apiserver.key -n monitoring kubectl get secret -n monitoring | grep volume-serving-cert kubectl get secret volume-serving-cert -n monitoring volume-serving-cert -o yaml
我是通过kubeadm安装的k8s，已经有了APIserver证书
[root@k8s-master ~]# cd /etc/kubernetes/ manifests/ pki/ [root@k8s-master ~]# cd /etc/kubernetes/pki/ [root@k8s-master pki]# ls apiserver.crt apiserver.key ca.crt front-proxy-ca.crt front-proxy-client.key serving.crt wx.crt apiserver-etcd-client.crt apiserver-kubelet-client.crt ca.key front-proxy-ca.key sa.key serving.csr wx.csr apiserver-etcd-client.key apiserver-kubelet-client.key etcd front-proxy-client.crt sa.pub serving.key wx.key [root@k8s-master pki]# [root@k8s-master pki]# kubectl create secret generic volume-serving-cert --from-file=apiserver.crt --from-file=apiserver.key -n monitoring secret/volume-serving-cert created [root@k8s-master pki]# kubectl get secret -n monitoring | grep volume-serving-cert volume-serving-cert Opaque 2 6s [root@k8s-master pki]# kubectl get secret volume-serving-cert -n monitoring volume-serving-cert -o yaml apiVersion: v1 items: - apiVersion: v1 data: apiserver.crt: LS0tLS1CRUdJTiBDRVJUSUZJQ0FURS0tLS0tCk1JSURXakNDQWtLZ0F3SUJBZ0lJYnQ4MS9hSW8xRGN3RFFZSktvWklodmNOQVFFTEJRQXdGVEVUTUJFR0ExVUUKQXhNS2EzVmlaWEp1WlhSbGN6QWVGdzB4T1RBNE1qa3dNVEl3TXpGYUZ3MHlNREE0TWpnd01USXdNekZhTUJreApGekFWQmdOVkJBTVREbXQxWW1VdFlYQnBjMlZ5ZG1WeU1JSUJJakFOQmdrcWhraUc5dzBCQVFFRkFBT0NBUThBCk1JSUJDZ0tDQVFFQXhzVGlsV0ZrSi82RnpRV21RNjA0NU9TYjRXcEowWGcwSDc3bW51dCtmOUVzRlRSQkMwQWcKTnBka09sZVN4aUt6Mi9GYXh2dndVZGtXaHBlY1hlT2xFbHM0VXlRanlpS …..
如果没有证书（参考）
#安装CFSSL工具 wget https://pkg.cfssl.org/R1.2/cfssl_linux-amd64 chmod +x cfssl_linux-amd64 mv cfssl_linux-amd64 /usr/local/bin/cfssl wget https://pkg.cfssl.org/R1.2/cfssljson_linux-amd64 chmod +x cfssljson_linux-amd64 mv cfssljson_linux-amd64 /usr/local/bin/cfssljson wget https://pkg.cfssl.org/R1.2/cfssl-certinfo_linux-amd64 chmod +x cfssl-certinfo_linux-amd64 mv cfssl-certinfo_linux-amd64 /usr/local/bin/cfssl-certinfo export PATH=/usr/local/bin:$PATH cd /etc/kubernetes/pki cat << EOF | tee apiserver.json { "CN": "apiserver", "hosts": [""], "key": { "algo": "rsa", "size": 2048 }, "names": [ { "C": "CN", "ST": "GuangDong", "L": "GuangZhou", "O": "wx", "OU": "wx" } ] } EOF ### 生成证书 cfssl gencert -ca=/apps/work/k8s/cfssl/pki/k8s/k8s-ca.pem -ca-key=/apps/work/k8s/cfssl/pki/k8s/k8s-ca-key.pem \ -config=/apps/work/k8s/cfssl/ca-config.json \ -profile=kubernetes /apps/work/k8s/cfssl/k8s/apiserver.json | cfssljson -bare ./apiserver ###重命名证书名字 mv apiserver-key.pem apiserver.key mv apiserver.pem apiserver.crt ### 创建secret kubectl create secret generic volume-serving-cert --from-file=apiserver.crt --from-file=apiserver.key -n monitoring kubectl get secret -n monitoring | grep volume-serving-cert kubectl get secret volume-serving-cert -n monitoring volume-serving-cert -o yaml
4.3 执行prometheus-adapter.yaml
[root@k8s-master pki]# cd /root/prometheus/kube-prometheus/manifests/prometheus-adapter/ [root@k8s-master prometheus-adapter]# ls prometheus-adapter-apiService.yaml prometheus-adapter-clusterRole.yaml prometheus-adapter-clusterRoleAggregatedMetricsReader.yaml prometheus-adapter-deployment.yaml prometheus-adapter-clusterRoleBindingDelegator.yaml prometheus-adapter-roleBindingAuthReader.yaml prometheus-adapter-clusterRoleBinding.yaml prometheus-adapter-serviceAccount.yaml prometheus-adapter-clusterRoleServerResources.yaml prometheus-adapter-service.yaml [root@k8s-master prometheus-adapter]# kubectl apply -f . apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created clusterrole.rbac.authorization.k8s.io/prometheus-adapter created clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created clusterrolebinding.rbac.authorization.k8s.io/prometheus-adapter created clusterrolebinding.rbac.authorization.k8s.io/resource-metrics:system:auth-delegator created clusterrole.rbac.authorization.k8s.io/resource-metrics-server-resources created deployment.apps/prometheus-adapter created rolebinding.rbac.authorization.k8s.io/resource-metrics-auth-reader created service/prometheus-adapter created serviceaccount/prometheus-adapter created [root@k8s-master prometheus-adapter]#
4.4 验证prometheus-adapter 部署是否正常
[root@k8s-master prometheus-adapter]# kubectl get pods -n monitoring -o wide | grep prometheus-adapter prometheus-adapter-668748ddbd-d9hxz 1/1 Running 0 6m55s 10.254.1.3 k8s-node-1 <none> <none> [root@k8s-master prometheus-adapter]# kubectl get service -n monitoring | grep prometheus-adapter prometheus-adapter ClusterIP 10.98.19.67 <none> 443/TCP 7m [root@k8s-master prometheus-adapter]# kubectl get --raw "/apis/custom.metrics.k8s.io" | jq . { "kind": "APIGroup", "apiVersion": "v1", "name": "custom.metrics.k8s.io", "versions": [ { "groupVersion": "custom.metrics.k8s.io/v1beta1", "version": "v1beta1" } ], "preferredVersion": { "groupVersion": "custom.metrics.k8s.io/v1beta1", "version": "v1beta1" } } [root@k8s-master prometheus-adapter]#
列出由prometheus提供的自定义指标：
kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1" | jq . { "kind": "APIResourceList", "apiVersion": "v1", "groupVersion": "custom.metrics.k8s.io/v1beta1", "resources": [ { "name": "nodes/kubelet_pleg_relist_duration_seconds_count", "singularName": "", "namespaced": true, "kind": "MetricValueList", "verbs": [ "get" ] }, { "name": "jobs.batch/node_memory_Active_file_bytes", "singularName": "", "namespaced": true, "kind": "MetricValueList", "verbs": [ "get" ] }, { "name": "namespaces/node_memory_PageTables_bytes", "singularName": "", "namespaced": false, "kind": "MetricValueList", "verbs": [ "get" …..
获取monitoring命名空间中所有pod的FS信息：
[root@k8s-master prometheus-adapter]# kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/monitoring/pods/*/fs_usage_bytes" | jq . { "kind": "MetricValueList", "apiVersion": "custom.metrics.k8s.io/v1beta1", "metadata": { "selfLink": "/apis/custom.metrics.k8s.io/v1beta1/namespaces/monitoring/pods/%2A/fs_usage_bytes" }, "items": [ { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "alertmanager-main-0", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "alertmanager-main-1", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "alertmanager-main-2", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "grafana-57bfdd47f8-d9fns", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "kube-state-metrics-ff5cb7949-lh945", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "node-exporter-9mhxs", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "node-exporter-csqzm", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "node-exporter-xc8tb", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "prometheus-adapter-668748ddbd-d9hxz", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "prometheus-k8s-0", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "prometheus-k8s-1", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "prometheus-operator-55b978b89-cgczz", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" }, { "describedObject": { "kind": "Pod", "namespace": "monitoring", "name": "redis-6dc489fd96-77np5", "apiVersion": "/v1" }, "metricName": "fs_usage_bytes", "timestamp": "2019-10-09T04:52:11Z", "value": "0" } ] }
如果有这些数据证明prometheus-adapter部署正常
5 使用官方测试hpa 项目测试自定义接口扩容
[root@k8s-master prometheus]# cd kube-prometheus/experimental/custom-metrics-api/ [root@k8s-master custom-metrics-api]# kubectl apply -f sample-app.yaml servicemonitor.monitoring.coreos.com/sample-app created service/sample-app created deployment.apps/sample-app created horizontalpodautoscaler.autoscaling/sample-app created [root@k8s-master custom-metrics-api]# kubectl get pod | grep sample-app sample-app-74684b97f-k5c5b 1/1 Running 0 17s [root@k8s-master custom-metrics-api]# kubectl get pod | grep sample-app kubectl get service | grep sample-app ^C [root@k8s-master custom-metrics-api]# kubectl get service | grep sample-app sample-app ClusterIP 10.106.102.68 <none> 8080/TCP 25s [root@k8s-master custom-metrics-api]# [root@k8s-master custom-metrics-api]# kubectl get hpa | grep sample-app sample-app Deployment/sample-app 264m/500m 1 10 1 52s [root@k8s-master custom-metrics-api]# [root@k8s-master custom-metrics-api]# curl 10.106.102.68:8080/metrics # HELP http_requests_total The amount of requests served by the server in total # TYPE http_requests_total counter http_requests_total 34
得到监控值http_requests_total
以后所有的监控值后面_total在这个接口都是去除的
kubectl get --raw"/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/*/http_requests"| jq .
[root@k8s-master custom-metrics-api]# kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/*/http_requests" | jq . { "kind": "MetricValueList", "apiVersion": "custom.metrics.k8s.io/v1beta1", "metadata": { "selfLink": "/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/%2A/http_requests" }, "items": [ { "describedObject": { "kind": "Pod", "namespace": "default", "name": "sample-app-74684b97f-k5c5b", "apiVersion": "/v1" }, "metricName": "http_requests", "timestamp": "2019-10-09T06:12:38Z", "value": "418m" } ] }
#测试自动伸缩 #安装hey go get -u github.com/rakyll/hey hey -n 10000 -q 5 -c 5 http://10.106.102.68:8080
几分钟后，HPA开始扩大部署。
ot@k8s-master custom-metrics-api]# kubectl get pod | grep sample-app sample-app-74684b97f-6gftk 0/1 ContainerCreating 0 2s sample-app-74684b97f-k5c5b 1/1 Running 0 4m5s sample-app-74684b97f-n5tvb 0/1 ContainerCreating 0 2s sample-app-74684b97f-sbkvn 0/1 ContainerCreating 0 2s [root@k8s-master custom-metrics-api]# kubectl get pod | grep sample-app sample-app-74684b97f-6gftk 1/1 Running 0 27s sample-app-74684b97f-6jg8x 1/1 Running 0 12s sample-app-74684b97f-gq622 1/1 Running 0 12s sample-app-74684b97f-k5c5b 1/1 Running 0 4m30s sample-app-74684b97f-n5tvb 1/1 Running 0 27s sample-app-74684b97f-sbkvn 1/1 Running 0 27s sample-app-74684b97f-x6thr 0/1 ContainerCreating 0 12s sample-app-74684b97f-zk9dz 1/1 Running 0 12s [root@k8s-master custom-metrics-api]# kubectl get pod | grep sample-app sample-app-74684b97f-6gftk 1/1 Running 0 67s sample-app-74684b97f-6jg8x 1/1 Running 0 52s sample-app-74684b97f-969vx 1/1 Running 0 36s sample-app-74684b97f-gq622 1/1 Running 0 52s sample-app-74684b97f-k5c5b 1/1 Running 0 5m10s sample-app-74684b97f-n5tvb 1/1 Running 0 67s sample-app-74684b97f-q8h2m 1/1 Running 0 36s sample-app-74684b97f-sbkvn 1/1 Running 0 67s sample-app-74684b97f-x6thr 0/1 ContainerCreating 0 52s sample-app-74684b97f-zk9dz 1/1 Running 0 52s [root@k8s-master custom-metrics-api]# [root@k8s-master custom-metrics-api]# kubectl get pod | grep sample-app sample-app-74684b97f-6gftk 1/1 Running 0 112s sample-app-74684b97f-6jg8x 1/1 Running 0 97s sample-app-74684b97f-969vx 1/1 Running 0 81s sample-app-74684b97f-gq622 1/1 Running 0 97s sample-app-74684b97f-k5c5b 1/1 Running 0 5m55s sample-app-74684b97f-n5tvb 1/1 Running 0 112s sample-app-74684b97f-q8h2m 1/1 Running 0 81s sample-app-74684b97f-sbkvn 1/1 Running 0 112s sample-app-74684b97f-x6thr 1/1 Running 0 97s sample-app-74684b97f-zk9dz 1/1 Running 0 97s [root@k8s-master custom-metrics-api]# [root@k8s-master ~]# kubectl get hpa | grep sample-app NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE sample-app Deployment/sample-app 4656m/500m 1 10 4 4m46s [root@k8s-master ~]# kubectl get hpa | grep sample-app sample-app Deployment/sample-app 3315m/500m 1 10 8 4m57s [root@k8s-master ~]# kubectl get hpa | grep sample-app sample-app Deployment/sample-app 3315m/500m 1 10 10 5m [root@k8s-master ~]# kubectl describe hpa podinfo sample-app [root@k8s-master ~]# kubectl describe hpa sample-app Name: sample-app Namespace: default Labels: <none> Annotations: kubectl.kubernetes.io/last-applied-configuration: {"apiVersion":"autoscaling/v2beta1","kind":"HorizontalPodAutoscaler","metadata":{"annotations":{},"name":"sample-app","namespace":"default... CreationTimestamp: Wed, 09 Oct 2019 14:10:28 +0800 Reference: Deployment/sample-app Metrics: ( current / target ) "http_requests" on pods: 2899m / 500m Min replicas: 1 Max replicas: 10 Deployment pods: 10 current / 10 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 pods metric http_requests ScalingLimited True TooManyReplicas the desired replica count is more than the maximum replica count Events: Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 4m52s horizontal-pod-autoscaler New size: 4; reason: pods metric http_requests above target Normal SuccessfulRescale 4m37s horizontal-pod-autoscaler New size: 8; reason: pods metric http_requests above target Normal SuccessfulRescale 4m21s horizontal-pod-autoscaler New size: 10; reason: pods metric http_requests above target [root@k8s-master ~]# #又过了N久之后
[root@k8s-master ~]# kubectl describe hpa sample-app | tail -10 Type Reason Age From Message ---- ------ ---- ---- ------- Normal SuccessfulRescale 35m horizontal-pod-autoscaler New size: 4; reason: pods metric http_requests above target Normal SuccessfulRescale 35m horizontal-pod-autoscaler New size: 8; reason: pods metric http_requests above target Normal SuccessfulRescale 35m horizontal-pod-autoscaler New size: 10; reason: pods metric http_requests above target Normal SuccessfulRescale 23m horizontal-pod-autoscaler New size: 8; reason: All metrics below target Normal SuccessfulRescale 18m horizontal-pod-autoscaler New size: 7; reason: All metrics below target Normal SuccessfulRescale 13m horizontal-pod-autoscaler New size: 6; reason: All metrics below target Normal SuccessfulRescale 8m18s horizontal-pod-autoscaler New size: 5; reason: All metrics below target Normal SuccessfulRescale 3m15s horizontal-pod-autoscaler New size: 4; reason: All metrics below target [root@k8s-master ~]# kubectl get pod | grep sample sample-app-74684b97f-6gftk 1/1 Running 0 36m sample-app-74684b97f-k5c5b 1/1 Running 0 40m sample-app-74684b97f-n5tvb 1/1 Running 0 36m sample-app-74684b97f-sbkvn 1/1 Running 0 36m [root@k8s-master ~]#
自动缩放器不会立即对使用峰值做出反应。默认情况下，度量标准同步每30秒发生一次，只有在最后5分钟内没有重新缩放时才能进行扩展/缩小。通过这种方式，HPA可以防止快速执行冲突的决策，并为Cluster Autoscaler提供时间。
阈值说明
m代表milli-units，例如，901m意味着milli-requests。
1000m=1
例如44315m/100 实际上是400个并发，阈值是100并发
[root@k8s-master custom-metrics-api]# kubectl get hpa NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE sample-app Deployment/sample-app 44315m/100 1 10 4 43m [root@k8s-master custom-metrics-api]#
例如设置成10000m，实际是10个并发，直接显示10
pods:
metricName: http_requests
targetAverageValue: 10000m
[root@k8s-master custom-metrics-api]# kubectl get hpa| grep sample sample-app Deployment/sample-app 212m/10 1 10 10 52m [root@k8s-master custom-metrics-api]#
