restful api访问k8s集群，增删改查信息，做界面二次开 发。
需要预先创建访问权限的配置。

官网api文档
https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.9/
版本更新到v1.10以后 上面这个链接就找不到了 要把v1.9改成v1.10才能访问。
https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.10/

下面罗列部分api

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

获取节点信息

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"},
...

获取namespace信息

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

获得quota信息

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

实践

k8s_master_ip:192.168.1.138
username 不同用户不同
password 不同用户不同
namespace 不同用户不同

1.查看容器

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  # > pods.txt 输出到 \\192.168.1.138\hadoop\info\pods.json了

看起来像是把所有的pod都拿出来了，包括活的和死的。
看了一下信息很多不过没有资源使用信息。

"phase": "Running"

这个是正在运行的pod

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

这种是删除了的，状态是failed 原因是被驱逐

增加continue参数取出正在运行的容器

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

2.查看资源总览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是限额  used是当前申请的限额
limits 和 requests 的区别是 limits是上限，不能突破，但不保证能给。 requests是下限，保证能给。 举例说明：一个容器 requests.memory 512Mi，limits.memory 1Gi。宿主机内存使用量高时，一定会留512Mi内存给这个容器，不一定能拿到1Gi内存。宿主机内存使用量低时，容器不能突破1Gi内存。
Gi 和 G 的区别是 Gi是1024进制，G是1000进制，M Mi也是同理。就像一个U盘8G但实际能使用的是7.45G(其实这里单位就是Gi)
pods是指容器，单位个
cpu单位 m指千分之一，200m即0.2个cpu。这是绝对值，不是相对值。比如0.1CPU不管是在单核或者多核机器上都是一样的，都严格等于0.1CPU core

实时数据

官方文档
https://kubernetes.io/docs/tasks/debug-application-cluster/core-metrics-pipeline/ 
https://github.com/kubernetes/metrics 
https://github.com/kubernetes-incubator/metrics-server

下载 metrics-server 压缩包文件
下载 googlecontainer/metrics-server-amd64:v0.2.0 
cd metrics-server-0.2.1/deploy
修改 metrics-server-deployment.yaml 文件 image 和 imagePullPolicy: IfNotPresent
kubectl create -f .

获取节点信息

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"}}
...]
}

获取pod信息

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"}}]}
...]
}

获取namespace信息
没找到url，就把上面获取pod的使用量全加起来就是namespace的使用量了

弃用的数据获取
参考 https://jimmysong.io/posts/using-heapster-to-get-object-metrics/
官方api文档 https://github.com/kubernetes/heapster/blob/master/docs/model.md 弃用了 
弃用的api取值 https://blog.csdn.net/mofiu/article/details/77126848

获取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/proxycurl -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"
}

本文转自CSDN-k8s api文档 调用heapster metrics