13-之容器资源需求、资源限制及Metric-server(Heapster)
目录
容器资源需求、资源限制及Heapster
容器的资源需求，资源限制
requests：需求，最低保障；
limits:限制，应限制；
CPU：
1颗逻辑CPU
500m=0.5CPU
内存：
E、P、T、G、M、K
Ei、Pi
QoS:
Guaranteed: 每个容器
同时设置CPU和内存的requests和limits。
cpu.limits=cpu.requests
memory.limits=memory.request
Burstable:
至少有一个容器设置CPU或内存资源的requests属性
BestEffort: 没有任何一个容器设置了requests或limits属性；最低优先级别；# 当节点资源匮乏时，为维护节点自身的安全，会回收一定的节点资源，这时优先级最低的pod最先被杀死。
Heapster
在k8s1.11之前使用heapster采集k8s集群内资源使用情况1.12版之后直接废弃heapster，之后使用metric-server
InfluxDB是一个时序数据库，为了将cAdvisor采集到的数据做存储，便于数据指标的持续展示。通过grafana接入InfluxDB数据源进行数据展示。
pod资源监控的大体行为可分为3类指标：
1.kubernetes系统指标
2.容器指标（cpu、内存的利用状况）
3.应用指标(业务指标：接受了多少用户请求、容器内部启动了多少个子进程处理请求)
部署InfluxDB
cat influxDB.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: monitoring-influxdb
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
task: monitoring
k8s-app: influxdb
template:
metadata:
labels:
task: monitoring
k8s-app: influxdb
spec:
containers:
- name: influxdb
image: k8s.gcr.io/heapster-influxdb-amd64:v1.5.2
volumeMounts:
- mountPath: /data
name: influxdb-storage
volumes:
- name: influxdb-storage
emptyDir: {} # 生产最好换成持久化存储
---
apiVersion: v1
kind: Service
metadata:
labels:
task: monitoring
# For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
# If you are NOT using this as an addon,you should comment out this line.
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: monitoring-infludb
spec:
ports:
- port: 8086
targetPort: 8086
selector:
k8s-app: influxdb
cat rbac.yaml
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
metadata:
name: heapster
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:heapster
subjects:
- kind: ServiceAccount
name: heapster
namespace: kube-system
cat heapster.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: heapster
namespace: kube-system
---
apiVersion: apps/v1
kind: Development
metadata:
name: heapster
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
task: monitoring
k8s-app: influxdb
template:
metadata:
labels:
task: monitoring
k8s-app: heapster
spec:
serviceAccountName: heapster
containers:
- name: heapster
image: k8s.gcr.io/heapster-amd64:v1.5.4
imagePullPolicy: IfNotPresent
command:
- /heapster
- --source=kubernetes:https://kubernetes.default
- --sink=influxdb:http//monitoring-influxdb.kube-system.svc:8086
---
apiVersion: v1
kind: Service
metadata:
labels:
task: monitoring
# For use as a CLuster add-on (https://github.com/kubernetes/tree/master/cluster/addons)
# If you are NOT using this as an addon,you should comment out this line.
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: Heapster
name: heapster
namespace: kube-system
spec:
ports:
- port: 80
targetPort: 8082
selector:
k8s-app: heapster
type: NodePort
apiVersion: apps/v1
kind: Deployment
metadata:
name: monitoring-grafana
namespace: kube-system
spec:
replicas: 1
selector:
matchLabels:
task: monitoring
k8s-app: influxdb
template:
metadata:
labels:
task: monitoring
k8s-app: grafana
spec:
containers:
- name: grafana
image: k8s.gcr.io/heapster-grafana-amd64:v5.0.4
ports:
- containerPort: 3000
protocol: TCP
volumeMounts:
- mountPath: /etc/ssl/certs
name: ca-certificates
readOnly: true
- mountPath: /var
name: grafana-storage
env:
- name: INFLUXDB_HOST
value: monitoring-influxdb
- name: GF_SERVER_HTTP_PORT
value: "3000"
# The followiing env variables are required to make Grafana accessible via
# the kubernetes api-server proxy. On production clusters,we recommend
# removing these env variables,setup auth for grafana,and expose the grafana
# service using a LoadBalancer or a public IP.
- name: GF_AUTH_BASIC_ENABLED
value: "false"
- name: GF_AUTH_ANONYMOUS_ORG_ROLE
value: Admin
- name: GF_AUTH_ANONYMOUS_ENABLED
value: "true"
- name: GF_SERVER_ROOT_URL
# If you;re only using the API Server proxy,set this value instead:
# value: /api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
value: /
volumes:
- name: ca-certificates
hostPath:
path: /etc/ssl/certs
- name: grafana-storage
emptyDir: {}
---
apiVersions: v1
kind: Service
metadata:
labels:
# For use as a Cluster add-on (https://github.com/kubernetes/kubernetes/tree/master/cluster/addons)
# If you are NOT using this as an addon, you should comment out this line.
kubernetes.io/cluster-service: 'true'
kubernetes.io/name: monitoring-grafana
name: monitoring-grafana
namespace: kube-system
spec:
# In a production setup,we recommend accessing Grafana through an external LoadBalancer
# Oor through a public IP.
# type: LoadBalancer
# you could also use NodePort to the service at a randonly gr=nerated port
# type: NodePort
ports:
- port: 80
targetPort: 3000
selector:
k8s-app: grafana
type: NodePort
资源指标API及自定义指标API
资源指标：metrics-server
自定义指标： prometheus,k8s-promethus-adapter
新一代架构：
核心指标流水线：由kubelet、metrics-server以及由API server提供的api组成；CPU累积使用率、Pod的资源占用率及容器的磁盘占用率；
监控流水线：用于从系统收集各种指标数据并提供终端用户、存储系统以及HPA，它们包含核心指标及许多非核心指标。非核心指标本身不能被k8s所解析。
metrics-server: API server,此API server 服务于资源指标的API服务，不是k8s的apiserver,
关于metrics-server镜像的下载，kubernetes官方已经把关于metrics-server附件(addons)的稳定版本添加到你核心附件，点击 metrics-servicer附件安装,可以进入kubernetes对应版本中下载yaml文件进行安装或者在此安装。本阶段使用的是k8s的1.22版本，对应metrics-server插件两个容器的版本是：
k8s.gcr.io/metrics-server/metrics-server:v0.5.2
k8s.gcr.io/autoscaling/addon-resizer:1.8.14
已经上传到dockerhub账号
在此版本之前，metrics-server容器的development YAML文件并没做存活性和就绪性探测；下面附上k8s 1.22版本的mtrics-server 的部署的yaml文件
[root@master01 addons_metrics-server]# cat auth-delegator.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: metrics-server:system:auth-delegator
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:auth-delegator
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
[root@master01 addons_metrics-server]# cat auth-reader.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: metrics-server-auth-reader
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
[root@master01 addons_metrics-server]# cat metrics-apiserver.yaml
apiVersion: apiregistration.k8s.io/v1
kind: APIService
metadata:
name: v1beta1.metrics.k8s.io
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
spec:
service:
name: metrics-server
namespace: kube-system
group: metrics.k8s.io
version: v1beta1
insecureSkipTLSVerify: true
groupPriorityMinimum: 100
versionPriority: 100
cat metrics-server-deployment.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
name: metrics-server
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
---
apiVersion: v1
kind: ConfigMap
metadata:
name: metrics-server-config
namespace: kube-system
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: EnsureExists
data:
NannyConfiguration: |-
apiVersion: nannyconfig/v1alpha1
kind: NannyConfiguration
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: metrics-server-v0.5.2
namespace: kube-system
labels:
k8s-app: metrics-server
addonmanager.kubernetes.io/mode: Reconcile
version: v0.5.2
spec:
selector:
matchLabels:
k8s-app: metrics-server
version: v0.5.2
template:
metadata:
name: metrics-server
labels:
k8s-app: metrics-server
version: v0.5.2
spec:
securityContext:
seccompProfile:
type: RuntimeDefault
priorityClassName: system-cluster-critical
serviceAccountName: metrics-server
nodeSelector:
kubernetes.io/os: linux
containers:
- name: metrics-server
#image: k8s.gcr.io/metrics-server/metrics-server:v0.5.2
image: v5cn/metrics-server:v0.5.2
command:
- /metrics-server
- --metric-resolution=30s
- --kubelet-use-node-status-port
- --kubelet-insecure-tls #
- --kubelet-preferred-address-types=InternalIP,Hostname,InternalDNS,ExternalDNS,ExternalIP
- --cert-dir=/tmp
- --secure-port=10250
ports:
- containerPort: 10250
name: https
protocol: TCP
readinessProbe:
httpGet:
path: /readyz
port: https
scheme: HTTPS
periodSeconds: 10
failureThreshold: 3
livenessProbe:
httpGet:
path: /livez
port: https
scheme: HTTPS
periodSeconds: 10
failureThreshold: 3
volumeMounts:
- mountPath: /tmp
name: tmp-dir
- name: metrics-server-nanny
image: k8s.gcr.io/autoscaling/addon-resizer:1.8.14
resources:
limits:
cpu: 100m
memory: 300Mi
requests:
cpu: 5m
memory: 50Mi
env:
- name: MY_POD_NAME
valueFrom:
fieldRef:
fieldPath: metadata.name
- name: MY_POD_NAMESPACE
valueFrom:
fieldRef:
fieldPath: metadata.namespace
volumeMounts:
- name: metrics-server-config-volume
mountPath: /etc/config
command:
- /pod_nanny
- --config-dir=/etc/config
# - --cpu={{ base_metrics_server_cpu }}
- --cpu=300m
- --extra-cpu=20m #0.5m
# - --memory={{ base_metrics_server_memory }}
- --memory=200Mi
# - --extra-memory={{ metrics_server_memory_per_node }}Mi
- --extra-memory=10Mi
- --threshold=5
- --deployment=metrics-server #-v0.5.2
- --container=metrics-server
- --poll-period=30000
- --estimator=exponential
# Specifies the smallest cluster (defined in number of nodes)
# resources will be scaled to.
#- --minClusterSize={{ metrics_server_min_cluster_size }}
- --minClusterSize=2
# Use kube-apiserver metrics to avoid periodically listing nodes.
- --use-metrics=true
volumes:
- name: metrics-server-config-volume
configMap:
name: metrics-server-config
- emptyDir: {}
name: tmp-dir
tolerations:
- key: "CriticalAddonsOnly"
operator: "Exists"
[root@master01 addons_metrics-server]# cat metrics-server-service.yaml
apiVersion: v1
kind: Service
metadata:
name: metrics-server
namespace: kube-system
labels:
addonmanager.kubernetes.io/mode: Reconcile
kubernetes.io/cluster-service: "true"
kubernetes.io/name: "Metrics-server"
spec:
selector:
k8s-app: metrics-server
ports:
- port: 443
protocol: TCP
targetPort: https
[root@master01 addons_metrics-server]# cat resource-reader.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: system:metrics-server
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
rules:
- apiGroups:
- ""
resources:
- pods
- nodes
- nodes/stats
- namespaces
verbs:
- get
- list
- watch
- apiGroups:
- "apps"
resources:
- deployments
verbs:
- get
- list
- update
- watch
- patch
- nonResourceURLs:
- /metrics
verbs:
- get
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: system:metrics-server
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:metrics-server
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
kubectl apply -f ./ # 部署metrics-server
kubectl get po -n kube-system
kubectl api-versions # 部署metrics-server之后新增加的api-->metrics.k8s.io/v1beta1
打开一个kube-apiserver的反代接口，通过curl获取api接口数据
kubectl proxy --port=8080
curl http://localhost:8080/apis/metrics.k8s.io/v1beta1
'''
{
"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"
]
}
]
}
'''
curl http://localhost:8080/apis/metrics.k8s.io/v1beta1/nodes
curl http://localhost:8080/apis/metrics.k8s.io/v1beta1/pods
kubectl top nodes
kubectl top pods -n kube-system
k8s-promtheus监控部署
node-exporter
cat node-exporter-ds.yaml
apiVersion: v1
kind: NameSpace
metadata:
name: prom
---
apiVersion: apps/v1
kind: DaemonSet
metadata:
name: prometheus-node-exporter
namespace: prom
labels:
app: prometheus
component: node-exporter
spec:
selector:
matchLabels:
app: prometheus
component: node-exporter
template:
metadata:
labels:
name: node-exporter
spec:
hostNetwork: true
hostPID: true
hostNetwork: true
tolerations:
- key: node-role.kubernetes.io/master
operator: "Exists"
effect: NoSchedule
containers:
- image: prom/node-exporter:v0.16.0
name: prometheus-node-exporter
ports:
- name: prom-node-exp
containerPort: 9100
hostPort: 9100
resources:
requests:
cpu: 0.15
securityContext:
privileged: true
args:
- --path.procfs
- /host/proc
- --path.sysfs
- /host/sys
- --collector.filesystem.ignored-mount-points
- '"^/(sys|proc|dev|host|etc)($|/)"'
volumeMounts:
- name: dev
mountPath: /host/dev
- name: proc
mountPath: /host/proc
- name: sys
mountPath: /host/sys
- name: rootfs
mountPath: /rootfs
volumes:
- name: proc
hostPath:
path: /proc
- name: dev
hostPath:
path: /dev
- name: sys
hostPath:
path: /sys
- name: rootfs
hostPath:
path: /
---
apiVersion: v1
kind: Service
metadata:
name: prometheus-node-exporter
namespace: prom
spec:
ports:
- port: 9100
targetPort: 9100
type: NodePort
selector:
app: prometheus
component: node-exporter
[root@master node_exporter]# kubectl apply -f ./
prometheus
cd /root/manifests/k8s-prom/prometheus && ls
prometheus-cfg.yaml prometheus-deploy.yaml prometheus-rbac.yaml prometheus-svc.yaml
cat prometheus-rbac.yaml
---
apiVersion: rbac.authorization.k8s.io/v1beta1
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"]
---
apiVersions: v1
kind: ServiceAccount
metadata:
name: prometheus
namespace: prom
---
apiVersions: rbac.authorization.k8s.io/vibeta1
kind: ClusterRoleBinding
metadata:
name: prometheus
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: prometheus
subjects:
- kind: ServiceAccount
name: prometheus
namespace: prom
cat prometheus-deploy.yaml
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: prometheus-server
namespace: prom
labels:
app: prometheus
spec:
replicas: 1
selector:
matchLabels:
app: prometheus
component: server
# matchExpressions:
#- {key:app, operator: In, values: [prometheus]}
#- {key: component, operator: In, values: [server]}
template:
metadata:
labels:
app: prometheus
component: server
annotations:
prometheus.io/scrape: 'false'
spec:
nodeName: node1
serviceAccountName: prometheus
containers:
- name: prometheus
image: prom/prometheus:v2.2.1
imagePullPolicy: IfNotPresent
command:
- prometheus
- --config.file=/etc/prometheus/promethus.yml
- --storage.tsdb.path=/prometheus
- --storage.tsdb.retention=720h
ports:
- containerPort: 9090
protocol: TCP
resources:
limits:
memory: 2Gi
volumeMounts:
- mountPath: /etc/prommetheus/prometheus.yml
name: prometheus-config
subPath: prometheus.yml
- mountPath: /prometheus/
name: prometheus-storage-volume
volumes:
- name: prometheus-config
configMap:
name: prometheus-config
items:
- key: prometheus.yml
path: prometheus.yml
mode: 0644
- name: prometheus-storage-volume
hostPath:
path: /data
type: Directory
kube-stats-metrics
k8s-prom-adapter
下载k8s-prom-adapter部署清单，和k8s-prom-adapter容器镜像
(umask 077; openssl genrsa -out serving.key 2048)
openssl req -new -key serving.key -out serving.csr -subj "/CN=serving"
openssl x509 -req in serving.csr -CA ./ca.crt -CAkey ./ca.key -CAcreateserial -out serving.crt -days 3650
kubectl create secret generic cm-adapter-serving-certs --from-file=serving.crt=./serving.crt --from-file=serving.key=serving.key -n prom
cd /root/manifests/k8s-prom/prometheus && ls
custom-metrics-apiserver-auth-delegator-cluster-role-binding.yaml
custom-metrics-apiserver-auth-reader-role-binding.yaml
custom-metrics-apiserver-deployment.yaml
custom-metrics-apiserver-resource-reader-cluster-role-binding.yaml
custom-metrics-apiserver-service-account.yaml
custom-metrics-apiserver-service.yaml
custom-metrics-apiservice.yaml
custom-metrics-cluster-role.yaml
custom-metrics-config-map.yaml
custom-metrics-resource-reader-cluster-role.yaml
hpa-custom-metrics-cluster-role-binding.yaml
cat custom-metrics-apiserver-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
labels:
app: custom-metrics-apiserver
name: custom-metrics-apiserver
namespace: prom
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: directxman12/k8s-prometheus-adapter-amd64
args:
- --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.prom.svc:9090/
- --metrics-relist-interval=1m
- --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
- mountPath: /tmp
name: tmp-vol
volumes:
- name: volume-serving-cert
secret:
secretName: cm-adapter-serving-certs
- name: config
configMap:
name: adapter-config
- name: tmp-vol
emptyDir: {}
kubectl apply -f ./
kubectl get all -n prom
kubectl api-versions
kubectl proxy --port=8080
curl http://localhost:8080/apis/custom.metrics.k8s.io/v1beta1/
HPA(HorizontalPodAutoscaler)
kubectl api-versions
kubectl explain hpa
apiVersion <string>
kind <string>
metadata <Object>
spec <Object>
maxReplicas <integer> -required-
minReplicas <integer>
targetCPUUtilizationPercentage <integer>
scaleTargetRef <Object> -required-
apiVersion <string>
kind <string> -required-
name <string> -required-
http://kubernetes.io/docs/user-guide/identifiers#names
创建一个静态pod
kubectl run myapp --image=nginx:1.20 --replicas=1 --requests='cpu=50m,memory=256Mi' --limits='cpu=50m,memory=256Mi' --labels='app=myapp' --expose --port=80
[root@master01 controll]# cat pod-deploy-autoscaling.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
name: myapp-deploy-autoscaling
namespace: default
spec:
replicas: 1
selector:
matchLabels:
app: myapp
template:
metadata:
name: myapp-deploy-controll
labels:
app: myapp
spec:
containers:
- name: myapp
image: nginx:1.20.2
ports:
- name: http
containerPort: 80
resources:
requests:
cpu: 50m
memory: 256Mi
limits:
cpu: 50m
memory: 256Mi
---
apiVersion: v1
kind: Service
metadata:
name: myapp-deploy-autoscaling
spec:
ports:
- port: 80
targetPort: 80
name: myapp-deploy-autoscaling
protocol: TCP
type: NodePort
selector:
app: myapp
kubectl apply -f pod-deploy-autoscaling.yaml
kubectl get po -o wide
kubectl get svc -o wide
curl 10.103.163.233:80 curl 192.168.1.130:30081
kubectl describe svc myapp-deploy-autoscaling
kubectl get po --show-labels
kubectl describe po myapp-deploy-autoscaling-8565bcd6d5-4nh57
创建一个hpa v1控制器
autoscale默认创建的是v1控制器。
kubectl autoscale deployment myapp-deploy-autoscaling --min=2 --max=6 --cpu-percent=60 # 当前控制器控制的一组pod的cpu使用率的平均值超过60%，开始扩充pod.
kubectl get hpa
kubectl get hpa myapp-deploy-autoscaling -o yaml
现在使用ab工具对service为myapp-deploy-autoscaling关联的一组pod进行压测，查看pod的自动动态水平扩充和缩减情况
kubectl get hpa -w
ab -c 100 -n 500000 http://192.168.1.130:30081/index.html
创建一个hpa v2控制器
删除hpa:
kubectl delete hpa myapp-deploy-autoscaling
v2控制器可以使用更多的指标，当作我们评估扩展时使用的指标
cat hpa-v2-demo.yaml
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: myapp-hpa-v2
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: myapp
minReplicas: 1
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
targetAverageUtilization: 55 # 百分比
- type: Resource
resource:
name: memory
targetAverageValue: 50Mi # pod内存超过50Mi,扩充pod.
kubectl apply -f hpa-v2-demo.yaml
kubectl get hpa
现在使用ab工具对service为myapp-deploy-autoscaling关联的一组pod进行压测，查看pod的自动动态水平扩充和缩减情况
kubectl get hpa -w
ab -c 100 -n 500000 http://192.168.1.130:30081/index.html
自定义hpa指标
根据pod中定义的指标限制pod的扩展。
cat hpa-v2-custom.yaml
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
metadata:
name: myapp-hpa-v2
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: myapp
minReplicas: 1
maxReplicas: 10
metrics:
- type: Pods
pods:
metricName: http_requests
targetAverageValue: 800m
