k8s restful api 訪問

API REST · 發表 2018-12-16 10:51:41

摘要： restful api訪問k8s叢集，增刪改查資訊，做介面二次開發。需要預先建立訪問許可權的配置。官網api文件 https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.9/ ...

restful api訪問k8s叢集，增刪改查資訊，做介面二次開發。

需要預先建立訪問許可權的配置。

官網api文件

ofollow,noindex" target="_blank">https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.9/

下面羅列部分api

curl -u admin:admin "https://localhost:6443/api/v1" -k
curl -u admin:admin "https://localhost:6443/api/v1/pods" -k

curl -u admin:admin "https://localhost:6443/api/v1/namespaces/{namespace}/pods" -k
curl -u admin:admin "https://localhost:6443/api/v1/namespaces/default/pods" -k

獲取節點資訊

curl -u admin:admin "https://localhost:6443/api/v1/nodes/{nodename}" -k
curl -u admin:admin "https://localhost:6443/api/v1/nodes/tensorflow1" -k
 
...
"status": {
"capacity": {
"cpu": "4",
"memory": "7970316Ki",
"pods": "110"
},
"allocatable": {
"cpu": "4",
"memory": "7867916Ki",
"pods": "110"
},
...

獲取namespace資訊

curl -u admin:admin "https://localhost:6443/api/v1/namespaces/{namespace}" -k
curl -u admin:admin "https://localhost:6443/api/v1/namespaces/default" -k

獲得quota資訊

curl -u admin:admin "https://localhost:6443/api/v1/namespaces/{namespace}/resourcequotas/" -k
curl -u admin:admin "https://localhost:6443/api/v1/namespaces/default/resourcequotas/" -k

實踐

k8s_master_ip:192.168.1.138

username 不同使用者不同

password 不同使用者不同

namespace 不同使用者不同

api地址

https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.10/

版本更新到v1.10以後上面這個連結就找不到了要把v1.9改成v1.10才能訪問。

檢視容器

curl -u {username}:{password} "https://{k8s_master_ip}:6443/api/v1/namespaces/{namespace}/pods/" -k
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/default/pods/" -k

看起來像是把所有的pod都拿出來了，包括活的和死的。

看了一下資訊很多不過沒有資源使用資訊。

"phase": "Running"

這個是正在執行的pod

"phase": "Failed"
"reason":"Evicted"

這種是刪除了的，狀態是failed 原因是被驅逐

增加continue引數取出正在執行的容器

curl -u {username}:{password} "https://{k8s_master_ip}:6443/api/v1/namespaces/{namespace}/pods?continue" -k
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/default/pods?continue" -k

檢視replicationcontroller
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/user1/replicationcontrollers/" -k

檢視service

curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/user1/services/" -k

檢視資源總覽resourcequotas

curl -u {username}:{password} "https://{k8s_master_ip}:6443/api/v1/namespaces/{namespace}/resourcequotas/" -k
[root@tensorflow1 info]# curl -u admin:admin "https://localhost:6443/api/v1/namespaces/default/resourcequotas/" -k
 
...
"status": {
"hard": {
"limits.cpu": "2",
"limits.memory": "6Gi",
"pods": "20",
"requests.cpu": "1",
"requests.memory": "1Gi"
},
"used": {
"limits.cpu": "400m",
"limits.memory": "1Gi",
"pods": "2",
"requests.cpu": "200m",
"requests.memory": "512Mi"
}
}
...

hard是限額 used是當前申請的限額

limits 和 requests 的區別是 limits是上限，不能突破，但不保證能給。 requests是下限，保證能給。舉例說明：一個容器 requests.memory 512Mi，limits.memory 1Gi。宿主機記憶體使用量高時，一定會留512Mi記憶體給這個容器，不一定能拿到1Gi記憶體。宿主機記憶體使用量低時，容器不能突破1Gi記憶體。

Gi 和 G 的區別是 Gi是1024進位制，G是1000進位制，M Mi也是同理。就像一個U盤8G但實際能使用的是7.45G(其實這裡單位就是Gi)

pods是指容器，單位個

cpu單位 m指千分之一，200m即0.2個cpu。這是絕對值，不是相對值。比如0.1CPU不管是在單核或者多核機器上都是一樣的，都嚴格等於0.1CPU core

實時資料

官方文件

https://kubernetes.io/docs/tasks/debug-application-cluster/core-metrics-pipeline/

https://github.com/kubernetes/metrics

https://github.com/kubernetes-incubator/metrics-server

下載 metrics-server 壓縮包檔案

下載 googlecontainer/metrics-server-amd64:v0.2.0

cd metrics-server-0.2.1/deploy

修改 metrics-server-deployment.yaml 檔案 image 和 imagePullPolicy: IfNotPresent

kubectl create -f .

獲取節點資訊

curl -u {username}:{password} "https://{k8s_master_ip}:6443/apis/metrics.k8s.io/v1beta1/nodes" -k
curl -u admin:admin "https://192.168.1.138:6443/apis/metrics.k8s.io/v1beta1/nodes" -k
 
{
"kind": "NodeMetricsList",
"apiVersion": "metrics.k8s.io/v1beta1",
"metadata": {
"selfLink": "/apis/metrics.k8s.io/v1beta1/nodes"
},
"items": [
...
{
"metadata": {
"name": "tensorflow1",
"selfLink": "/apis/metrics.k8s.io/v1beta1/nodes/tensorflow1",
"creationTimestamp": "2018-04-09T08:44:17Z"
},
"timestamp": "2018-04-09T08:44:00Z",
"window": "1m0s",
"usage": {
"cpu": "265m",
"memory": "3448228Ki"
}
}
...
]
}

獲取pod資訊

curl -u {username}:{password} "https://{k8s_master_ip}:6443/apis/metrics.k8s.io/v1beta1/namespaces/{namespace}/pods" -k
curl -u admin:admin "https://192.168.1.138:6443/apis/metrics.k8s.io/v1beta1/namespaces/default/pods" -k
 
{
"kind": "PodMetricsList",
"apiVersion": "metrics.k8s.io/v1beta1",
"metadata": {
"selfLink": "/apis/metrics.k8s.io/v1beta1/namespaces/default/pods"
},
"items": [
...
{
"metadata": {
"name": "tensorflow-worker-rc-998wf",
"namespace": "default",
"selfLink": "/apis/metrics.k8s.io/v1beta1/namespaces/default/pods/tensorflow-worker-rc-998wf",
"creationTimestamp": "2018-04-09T08:52:38Z"
},
"timestamp": "2018-04-09T08:52:00Z",
"window": "1m0s",
"containers": [
{
"name": "worker",
"usage": {
"cpu": "0",
"memory": "39964Ki"
}
}
]
}
...
]
}

獲取namespace資訊

沒找到url，就把上面獲取pod的使用量全加起來就是namespace的使用量了

Metrics API 文件

網上找不到文件只能從 kubectl top 命令幫助裡找

[root@tensorflow1 ~]# kubectl top
Display Resource (CPU/Memory/Storage) usage.
 
The top command allows you to see the resource consumption for nodes or pods.
 
This command requires Heapster to be correctly configured and working on the server.
 
Available Commands:
nodeDisplay Resource (CPU/Memory/Storage) usage of nodes
podDisplay Resource (CPU/Memory/Storage) usage of pods
 
Usage:
kubectl top [options]
 
Use "kubectl <command> --help" for more information about a given command.
Use "kubectl options" for a list of global command-line options (applies to all commands).

[root@tensorflow1 ~]# kubectl top pod --help
Display Resource (CPU/Memory/Storage) usage of pods.
 
The 'top pod' command allows you to see the resource consumption of pods.
 
Due to the metrics pipeline delay, they may be unavailable for a few minutes since pod creation.
 
Aliases:
pod, pods, po
 
Examples:
# Show metrics for all pods in the default namespace
kubectl top pod

# Show metrics for all pods in the given namespace
kubectl top pod --namespace=NAMESPACE

# Show metrics for a given pod and its containers
kubectl top pod POD_NAME --containers

# Show metrics for the pods defined by label name=myLabel
kubectl top pod -l name=myLabel
 
Options:
--all-namespaces=false: If present, list the requested object(s) across all namespaces. Namespace in current
context is ignored even if specified with --namespace.
--containers=false: If present, print usage of containers within a pod.
--heapster-namespace='kube-system': Namespace Heapster service is located in
--heapster-port='': Port name in service to use
--heapster-scheme='http': Scheme (http or https) to connect to Heapster as
--heapster-service='heapster': Name of Heapster service
-l, --selector='': Selector (label query) to filter on, supports '=', '==', and '!='.(e.g. -l key1=value1,key2=value2)
 
Usage:
kubectl top pod [NAME | -l label] [options]
 
Use "kubectl options" for a list of global command-line options (applies to all commands).

棄用的資料獲取

參考 https://jimmysong.io/posts/using-heapster-to-get-object-metrics/

官方api文件 https://github.com/kubernetes/heapster/blob/master/docs/model.md 棄用了

棄用的api取值 https://blog.csdn.net/mofiu/article/details/77126848

獲取heapster url
[root@tensorflow1 influxdb]kubectl cluster-info
Kubernetes master is running at https://192.168.1.138:6443
Heapster is running at https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/heapster/proxy
KubeDNS is running at https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy
monitoring-grafana is running at https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/monitoring-grafana/proxy
monitoring-influxdb is running at https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/monitoring-influxdb/proxy
 
 
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/heapster/proxy/api/v1/model/namespaces/" -k
 
 
curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/heapster/proxy/api/v1/model/namespaces/default/metrics" -k
[
"memory/request",
"memory/limit",
"cpu/usage_rate",
"memory/usage",
"cpu/request",
"cpu/limit"
]
[root@tensorflow1 influxdb]# curl -u admin:admin "https://192.168.1.138:6443/api/v1/namespaces/kube-system/services/heapster/proxy/api/v1/model/namespaces/default/metrics/memory/usage" -k
{
"metrics": [
...
{
"timestamp": "2018-04-09T07:45:00Z",
"value": 81121280
},
{
"timestamp": "2018-04-09T07:46:00Z",
"value": 81121280
}
...
],
"latestTimestamp": "2018-04-09T07:46:00Z"
}

本文轉自CSDN-k8s restful api 訪問

k8s restful api 訪問

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