09-4.部署 metrics-server 插件
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09-4.部署 metrics-server 插件
创建 metrics-server 使用的证书
创建 metrics-server 证书签名请求:
cat > metrics-server-csr.json <<EOF
"CN": "aggregator",
"hosts": [],
"key":
"algo": "rsa",
"size": 2048
,
"names": [
"C": "CN",
"ST": "BeiJing",
"L": "BeiJing",
"O": "k8s",
"OU": "4Paradigm"
]
EOF
- 注意: CN 名称为 aggregator,需要与 kube-apiserver 的 --requestheader-allowed-names 参数配置一致;
生成 metrics-server 证书和私钥:
cfssl gencert -ca=/etc/kubernetes/cert/ca.pem -ca-key=/etc/kubernetes/cert/ca-key.pem -config=/etc/kubernetes/cert/ca-config.json -profile=kubernetes metrics-server-csr.json | cfssljson -bare metrics-server
将生成的证书和私钥文件拷贝到 kube-apiserver 节点:
source /opt/k8s/bin/environment.sh
for node_ip in $NODE_IPS[@]
do
echo ">>> $node_ip"
scp metrics-server*.pem [email protected]$node_ip:/etc/kubernetes/cert/
done
修改 kubernetes 控制平面组件的配置以支持 metrics-server
kube-apiserver
添加如下配置参数:
--requestheader-client-ca-file=/etc/kubernetes/cert/ca.pem
--requestheader-allowed-names=""
--requestheader-extra-headers-prefix="X-Remote-Extra-"
--requestheader-group-headers=X-Remote-Group
--requestheader-username-headers=X-Remote-User
--proxy-client-cert-file=/etc/kubernetes/cert/metrics-server.pem
--proxy-client-key-file=/etc/kubernetes/cert/metrics-server-key.pem
--runtime-config=api/all=true
--requestheader-XXX
、--proxy-client-XXX
是 kube-apiserver 的 aggregator layer 相关的配置参数,metrics-server & HPA 需要使用;--requestheader-client-ca-file
:用于签名--proxy-client-cert-file
和--proxy-client-key-file
指定的证书;在启用了 metric aggregator 时使用;- 如果 --requestheader-allowed-names 不为空,则--proxy-client-cert-file 证书的 CN 必须位于 allowed-names 中,默认为 aggregator;
如果 kube-apiserver 机器没有运行 kube-proxy,则还需要添加 --enable-aggregator-routing=true
参数;
关于 --requestheader-XXX
相关参数,参考:
- https://github.com/kubernetes-incubator/apiserver-builder/blob/master/docs/concepts/auth.md
- https://docs.bitnami.com/kubernetes/how-to/configure-autoscaling-custom-metrics/
注意:requestheader-client-ca-file 指定的 CA 证书,必须具有 client auth and server auth;
kube-controllr-manager
添加如下配置参数:
--horizontal-pod-autoscaler-use-rest-clients=true
用于配置 HPA 控制器使用 REST 客户端获取 metrics 数据。
整体架构
修改插件配置文件配置文件
metrics-server 插件位于 kubernetes 的 cluster/addons/metrics-server/
目录下。
修改 metrics-server-deployment 文件:
$ cp metrics-server-deployment.yaml,.orig
$ diff metrics-server-deployment.yaml.orig metrics-server-deployment.yaml
51c51
< image: mirrorgooglecontainers/metrics-server-amd64:v0.2.1
---
> image: k8s.gcr.io/metrics-server-amd64:v0.2.1
54c54
< - --source=kubernetes.summary_api:‘‘
---
> - --source=kubernetes.summary_api:https://kubernetes.default?kubeletHttps=true&kubeletPort=10250
60c60
< image: siriuszg/addon-resizer:1.8.1
---
> image: k8s.gcr.io/addon-resizer:1.8.1
- metrics-server 的参数格式与 heapster 类似。由于 kubelet 只在 10250 监听 https 请求,故添加相关参数;
授予 kube-system:metrics-server ServiceAccount 访问 kubelet API 的权限:
$ cat auth-kubelet.yaml
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: metrics-server:system:kubelet-api-admin
labels:
kubernetes.io/cluster-service: "true"
addonmanager.kubernetes.io/mode: Reconcile
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:kubelet-api-admin
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
- 新建一个 ClusterRoleBindings 定义文件,授予相关权限;
创建 metrics-server
$ pwd
/opt/k8s/kubernetes/cluster/addons/metrics-server
$ ls -l *.yaml
-rw-rw-r-- 1 k8s k8s 398 Jun 5 07:17 auth-delegator.yaml
-rw-rw-r-- 1 k8s k8s 404 Jun 16 18:02 auth-kubelet.yaml
-rw-rw-r-- 1 k8s k8s 419 Jun 5 07:17 auth-reader.yaml
-rw-rw-r-- 1 k8s k8s 393 Jun 5 07:17 metrics-apiservice.yaml
-rw-rw-r-- 1 k8s k8s 2640 Jun 16 17:54 metrics-server-deployment.yaml
-rw-rw-r-- 1 k8s k8s 336 Jun 5 07:17 metrics-server-service.yaml
-rw-rw-r-- 1 k8s k8s 801 Jun 5 07:17 resource-reader.yaml
$ kubectl create -f .
查看运行情况
$ kubectl get pods -n kube-system |grep metrics-server
metrics-server-v0.2.1-7486f5bd67-v95q2 2/2 Running 0 45s
$ kubectl get svc -n kube-system|grep metrics-server
metrics-server ClusterIP 10.254.115.120 <none> 443/TCP 1m
查看 metrcs-server 输出的 metrics
metrics-server 输出的 APIs:https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/resource-metrics-api.md
-
通过 kube-apiserver 或 kubectl proxy 访问:
https://192.168.1.106:6443/apis/metrics.k8s.io/v1beta1/nodes
https://192.168.1.106:6443/apis/metrics.k8s.io/v1beta1/nodes/
https://192.168.1.106:6443/apis/metrics.k8s.io/v1beta1/pods
https://192.168.1.106:6443/apis/metrics.k8s.io/v1beta1/namespace//pods/ -
直接使用 kubectl 命令访问:
kubectl get --raw apis/metrics.k8s.io/v1beta1/nodes
kubectl get --raw apis/metrics.k8s.io/v1beta1/pods
kubectl get --raw apis/metrics.k8s.io/v1beta1/nodes/
kubectl get --raw apis/metrics.k8s.io/v1beta1/namespace//pods/
$ 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"
]
]
$ kubectl get --raw "/apis/metrics.k8s.io/v1beta1/nodes" | jq .
"kind": "NodeMetricsList",
"apiVersion": "metrics.k8s.io/v1beta1",
"metadata":
"selfLink": "/apis/metrics.k8s.io/v1beta1/nodes"
,
"items": [
"metadata":
"name": "kube-node3",
"selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/kube-node3",
"creationTimestamp": "2018-06-16T10:24:03Z"
,
"timestamp": "2018-06-16T10:23:00Z",
"window": "1m0s",
"usage":
"cpu": "133m",
"memory": "1115728Ki"
,
"metadata":
"name": "kube-node1",
"selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/kube-node1",
"creationTimestamp": "2018-06-16T10:24:03Z"
,
"timestamp": "2018-06-16T10:23:00Z",
"window": "1m0s",
"usage":
"cpu": "221m",
"memory": "6799908Ki"
,
"metadata":
"name": "kube-node2",
"selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/kube-node2",
"creationTimestamp": "2018-06-16T10:24:03Z"
,
"timestamp": "2018-06-16T10:23:00Z",
"window": "1m0s",
"usage":
"cpu": "76m",
"memory": "1130180Ki"
]
- /apis/metrics.k8s.io/v1beta1/nodes 和 /apis/metrics.k8s.io/v1beta1/pods 返回的 usage 包含 CPU 和 Memory;
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