当您发出kubectl top node 时,kubectl 会向多个端点发出多个 HTTP 请求。您可以通过将--v=9 标志添加到kubectl 来查看确切的端点。
以我为例
kubectl top node gke-cluster-1-default-pool-99238d56-bv6z --v=9
[...]
I0726 10:41:18.347144 1986 round_trippers.go:435] curl -k -v -XGET -H "Accept: application/json, */*" -H "User-Agent: kubectl/v1.21.0 (linux/amd64) kubernetes/cb303e6" 'https://<ip-address>/apis/metrics.k8s.io/v1beta1/nodes/gke-cluster-1-default-pool-99238d56-bv6z'
I0726 10:41:18.489068 1986 round_trippers.go:435] curl -k -v -XGET -H "Accept: application/json, */*" -H "User-Agent: kubectl/v1.21.0 (linux/amd64) kubernetes/cb303e6" 'https://<ip-address>/api/v1/nodes/gke-cluster-1-default-pool-99238d56-bv6z'
[...]
(还有很多,这两个对于回答你的问题很重要)
第一次请求返回
{
"kind":"NodeMetrics",
"apiVersion":"metrics.k8s.io/v1beta1",
"metadata":{
"name":"gke-cluster-1-default-pool-99238d56-bv6z",
"selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/gke-cluster-1-default-pool-99238d56-bv6z",
"creationTimestamp":"2021-07-26T08:41:19Z"
},
"timestamp":"2021-07-26T08:41:07Z",
"window":"30s",
"usage":{
"cpu":"86855567n",
"memory":"950228Ki"
}
}
.usage.cpu 和 .usage.memory 分别显示使用的 CPU 和内存。
第二次请求返回(截断,响应很大)
{
"status":{
"capacity":{
"attachable-volumes-gce-pd":"15",
"cpu":"2",
"ephemeral-storage":"98868448Ki",
"hugepages-1Gi":"0",
"hugepages-2Mi":"0",
"memory":"4031624Ki",
"pods":"110"
},
"allocatable":{
"attachable-volumes-gce-pd":"15",
"cpu":"940m",
"ephemeral-storage":"47093746742",
"hugepages-1Gi":"0",
"hugepages-2Mi":"0",
"memory":"2885768Ki",
"pods":"110"
}
}
}
.status.allocatable.cpu 和 .status.allocatable.memory 显示可以为运行中的 pod 分配多少 CPU 和内存。
如您所见,没有以百分比返回使用情况的端点,kubectl 会即时进行计算,以人类友好的格式输出结果
$ kubectl top node gke-cluster-1-default-pool-99238d56-bv6z
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
gke-cluster-1-default-pool-99238d56-bv6z 108m 11% 928Mi 32%