Custom HPA水平自动伸缩

简介

Custom HPA 是Kubernetes中Pod水平自动伸缩的一种,不同于标准的HPA基于Pod的CPU使用率和内存使用量来控制工作负载中的副本数量,Custom HPA支持以自定义监控指标来实现对工作负载中副本数的控制

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目前社区提供了基于Prometheus的Costom HPA方案,方案中包含以下组件:

  • Prometheus:云原生监控告警系统,用于周期性采集Pod中的自定义监控数据
  • Prometheus Adapter: Prometheus适配器,用于将接收到custom metric api 请求转换成 promethus请求,并将prometheus 返回的数据转换成 custom metric api 定义的标准数据格式
  • Metrics aggreagtor:Kubernetes API 汇聚层中的一部分,用于将外部监控服务集成到 kube-apiserver中
  • Horizontal Pod AutoScaler: Pod水平自动伸缩功能的核心服务,周期性获取HPA实例中定义的监控指标数据,对比定义中的期望值,动态调整工作负载中的副本数量

基于Promethus的Custom HPA 部署实践

安装Helm V2

在Kubernetes集群内任意节点上执行如下命令,安装helm client

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# 下载Helm二进制文件
$ wget https://get.helm.sh/helm-v2.16.1-linux-amd64.tar.gz

# 解压缩helm-v2.16.1-linux-amd64.tar.gz
$ tar zxvf helm-v2.16.1-linux-amd64.tar.gz

# 将Helm 二进制文件拷贝至 /usr/local/bin目录下
$ mv ~/linux-amd64/helm /usr/local/bin

安装Helm 服务端组件Tiller

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# 创建 ServiceAccount
$ kubectl create serviceaccount tiller --namespace=kube-system

# 赋予tiller admin权限
$ kubectl create clusterrolebinding tiller-admin --serviceaccount=kube-system:tiller --clusterrole=cluster-admin

# 使用 tiller ServiceAccount 部署安装 Tiller
$ helm init --service-account=tiller --tiller-image=hub.ksyun.com/docker/tiller:v2.16.1 --skip-refresh

# 查看tiller-deploy是否创建成功
$ kubectl get deploy tiller-deploy -n kube-system

helm 官方源 https://kubernetes-charts.storage.googleapis.com ,国内的某些机器无法访问,需要配置镜像源

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# Azure 镜像
$ helm repo add stable http://mirror.azure.cn/kubernetes/charts/
$ helm repo add incubator http://mirror.azure.cn/kubernetes/charts-incubator/

# 更新源
$ helm repo update

开启Kubernetes API聚合层

在集群master节点修改 kube-apiserver.yaml 配置如下启动项

注意:K8S集群默认现已开启 Kubernetes API 聚合层,用户无需手动配置

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# vi /etc/kubernetes/manifests/kube-apiserver.yaml
apiVersion: v1
kind: Pod
metadata:
annotations:
scheduler.alpha.kubernetes.io/critical-pod: ""
creationTimestamp: null
labels:
component: kube-apiserver
tier: control-plane
name: kube-apiserver
namespace: kube-system
containers:
- command:
...
# 加入以下配置
- --requestheader-client-ca-file=/etc/kubernetes/ssl/aggregator/aggregator-ca.pem
- --proxy-client-cert-file=/etc/kubernetes/ssl/aggregator/aggregator.pem
- --proxy-client-key-file=/etc/kubernetes/ssl/aggregator/aggregator-key.pem
- --requestheader-allowed-names=aggregator
- --requestheader-extra-headers-prefix=X-Remote-Extra-
- --requestheader-group-headers=X-Remote-Group
- --requestheader-username-headers=X-Remote-User

部署Prometheus

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# 创建命名空间
$ kubectl create namespace monitoring

# 创建StorageClass
$ kubectl apply -f storageclass.yaml

# 使用Kubernetes charts仓库中prometheus的chart包进行安装
$ helm install stable/prometheus --namespace monitoring --values prom-values.yaml --name prometheus

部署Prometheus Adapter

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$ helm install stable/prometheus-adapter --values adapter-values.yaml --name prometheus-adapter --namespace monitoring

备注:启动时,–v=6 可以打印出adapter请求prometheus的query信息

验证Prometheus Adapter服务是否可用

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$ kubectl get apiservice | grep prometheus-adapter
NAME SERVICE AVAILABLE AGE
v1beta1.custom.metrics.k8s.io monitoring/prometheus-adapter True 3h42m

自定义HPA功能验证

部署测试服务

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apiVersion: apps/v1
kind: Deployment
metadata:
name: hpa-prom-demo
spec:
selector:
matchLabels:
app: nginx-server
template:
metadata:
prometheus.io/scrape: "true"
prometheus.io/port: "80"
prometheus.io/path: "/status/format/prometheus"
labels:
app: nginx-server
spec:
containers:
- name: nginx-demo
image: cnych/nginx-vts:v1.0
resources:
limits:
cpu: 50m
requests:
cpu: 50m
ports:
- containerPort: 80
name: http
---
apiVersion: v1
kind: Service
metadata:
name: hpa-prom-demo
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "80"
prometheus.io/path: "/status/format/prometheus"
spec:
ports:
- port: 80
targetPort: 80
name: http
selector:
app: nginx-server
type: NodePort

查询测试服务提供的自定义监控数据

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export DEMO_SVC_IP=$(kubectl get svc  hpa-prom-demo -o jsonpath='{.spec.clusterIP}')
export DEMO_SVC_PORT=$(kubectl get svc hpa-prom-demo -o jsonpath='{.spec.ports[0].port}')

curl http://${DEMO_SVC_IP}:${DEMO_SVC_PORT}/status/format/prometheus | grep nginx_vts_server_requests_total
nginx_vts_server_requests_total{host="*",code="1xx"} 0
nginx_vts_server_requests_total{host="*",code="2xx"} 13328
nginx_vts_server_requests_total{host="*",code="3xx"} 0
nginx_vts_server_requests_total{host="*",code="4xx"} 0
nginx_vts_server_requests_total{host="*",code="5xx"} 0
nginx_vts_server_requests_total{host="*",code="total"} 13328
...

创建HPA

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apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: nginx-custom-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: hpa-prom-demo
minReplicas: 2
maxReplicas: 10
metrics:
- type: Pods
pods:
metricName: nginx_vts_server_requests_per_second # 自定义指标项 —— nginx_vts_server每秒请求数
targetAverageValue: 4000m # 期望平均每秒请求数量为 4000m 即 4个请求/秒

设置Prometheus Adapter查询规则

修改 prometheus adapter configmap 定义自定义指标查询规则,根据自定义监控指标需要配置指定查询规则,建议去掉冗余的查询规则

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$ kubectl edit cm prometheus-adapter -n monitoring
config.yaml: |
rules:
- seriesQuery: 'nginx_vts_server_requests_total'
resources:
overrides:
kubernetes_namespace:
resource: namespace
kubernetes_pod_name:
resource: pod
name:
matches: "^(.*)_total"
as: "${1}_per_second"
metricsQuery: (sum(rate(<<.series>>{<<.labelmatchers>>,code!="", kubernetes_pod_name!="",code!="total",host!="_"}[2m])) by (<<.groupby>>))

配置参数使用说明
配置范例

查询自定义监控指标项,验证配置的查询规则是否生效

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kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/" | jq .
{
"kind": "APIResourceList",
"apiVersion": "v1",
"groupVersion": "custom.metrics.k8s.io/v1beta1",
"resources": [
{
"name": "namespaces/nginx_vts_server_requests_per_second",
"singularName": "",
"namespaced": false,
"kind": "MetricValueList",
"verbs": [
"get"
]
},
{
"name": "pods/nginx_vts_server_requests_per_second",
"singularName": "",
"namespaced": true,
"kind": "MetricValueList",
"verbs": [
"get"
]
}
]
}

查询自定义监控指标数据

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kubectl get --raw "/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/*/nginx_vts_server_requests_per_second" | jq .
{
"kind": "MetricValueList",
"apiVersion": "custom.metrics.k8s.io/v1beta1",
"metadata": {
"selfLink": "/apis/custom.metrics.k8s.io/v1beta1/namespaces/default/pods/%2A/nginx_vts_server_requests_per_second"
},
"items": [
{
"describedObject": {
"kind": "Pod",
"namespace": "default",
"name": "hpa-prom-demo-547b49c5c9-6dmgj",
"apiVersion": "/v1"
},
"metricName": "nginx_vts_server_requests_per_second",
"timestamp": "2020-08-13T06:50:22Z",
"value": "33m",
"selector": null
},
{
"describedObject": {
"kind": "Pod",
"namespace": "default",
"name": "hpa-prom-demo-547b49c5c9-8zdt4",
"apiVersion": "/v1"
},
"metricName": "nginx_vts_server_requests_per_second",
"timestamp": "2020-08-13T06:50:22Z",
"value": "33m",
"selector": null
}
]
}

对测试服务进行模拟压力测试

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export SERVICE_CLUSTER_IP=$(kubectl get svc hpa-prom-demo -o jsonpath='{.spec.clusterIP}')
$ hey -z 10m -q 50 -c 10 -m GET http://${SERVICE_CLUSTER_IP}

参数说明:

  • -z : 压测持续时间
  • -q : 单worker每秒请求数量(QPS)
  • -c : worker数量

查看测试服务deploy的副本数

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$ kubectl get deploy  hpa-prom-demo -w
NAME READY UP-TO-DATE AVAILABLE AGE
hpa-prom-demo 2/4 2 2 2d21h
hpa-prom-demo 2/4 4 2 2d21h
hpa-prom-demo 3/4 4 3 2d21h
hpa-prom-demo 4/4 4 4 2d21h
hpa-prom-demo 4/8 4 4 2d21h
hpa-prom-demo 4/8 4 4 2d21h
hpa-prom-demo 4/8 8 4 2d21h
hpa-prom-demo 5/8 8 5 2d21h
hpa-prom-demo 6/8 8 6 2d21h
hpa-prom-demo 7/8 8 7 2d21h
hpa-prom-demo 8/8 8 8 2d21h
hpa-prom-demo 8/10 8 8 2d21h
hpa-prom-demo 8/10 8 8 2d21h
hpa-prom-demo 9/10 10 9 2d21h
hpa-prom-demo 10/10 10 10 2d21h

查看HPA事件信息

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$ kubectl get hpa nginx-custom-hpa
NAME REFERENCE TARGETS MINPODS MAXPODS REPLICAS AGE
nginx-custom-hpa Deployment/hpa-prom-demo 96953m/4 2 10 10 47h


$ kubectl describe hpa nginx-custom-hpa
...
Conditions:
Type Status Reason Message
---- ------ ------ -------
AbleToScale True ReadyForNewScale recommended size matches current size
ScalingActive True ValidMetricFound the HPA was able to successfully calculate a replica count from pods metric nginx_vts_server_requests_per_second
ScalingLimited True TooManyReplicas the desired replica count is more than the maximum replica count
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal SuccessfulRescale 47h horizontal-pod-autoscaler New size: 2; reason: Current number of replicas below Spec.MinReplicas
Normal SuccessfulRescale 47h horizontal-pod-autoscaler New size: 9; reason: All metrics below target
Normal SuccessfulRescale 47h horizontal-pod-autoscaler New size: 7; reason: All metrics below target
Normal SuccessfulRescale 47h horizontal-pod-autoscaler New size: 2; reason: All metrics below target
Normal SuccessfulRescale 6m20s (x2 over 47h) horizontal-pod-autoscaler New size: 4; reason: pods metric nginx_vts_server_requests_per_second above target
Normal SuccessfulRescale 6m5s (x2 over 47h) horizontal-pod-autoscaler New size: 8; reason: pods metric nginx_vts_server_requests_per_second above target
Normal SuccessfulRescale 5m50s (x2 over 47h) horizontal-pod-autoscaler New size: 10; reason: pods metric nginx_vts_server_requests_per_second above targetnginx_vts_server_requests_per_second above target
Normal SuccessfulRescale 48m horizontal-pod-autoscaler New size: 2; reason: All metrics below target