kubectl top

Find the node across all cluster1, cluster3, and cluster4 that consumes the most CPU and store the result to the file /opt/high_cpu_node in the following format cluster_name,node_name. The node could be in any clusters that are currently configured on the student-node.

student-node ~ ➜  ssh cluster1-controlplane "kubectl top node"
NAME                    CPU(cores)   CPU(%)   MEMORY(bytes)   MEMORY(%)   
cluster1-controlplane   572m         1%       1071Mi          0%          
cluster1-node01         81m          0%       1155Mi          0%          
cluster1-node02         59m          0%       716Mi           0%          

student-node ~ ✖ ssh cluster3-controlplane "kubectl top node"
NAME                    CPU(cores)   CPU(%)   MEMORY(bytes)   MEMORY(%)   
cluster3-controlplane   96m          0%       1880Mi          1%          

student-node ~ ➜  ssh cluster4-controlplane "kubectl top node"
NAME                    CPU(cores)   CPU(%)   MEMORY(bytes)   MEMORY(%)   
cluster4-controlplane   166m         0%       1072Mi          0%          
cluster4-node01         86m          0%       1064Mi          0%

student-node ~ ➜  echo "cluster1,cluster1-controlplane" > /opt/high_cpu_node

Pod usage script

Script /opt/course/7/pod.sh should show resource usage of Pods and their containers.

kubectl top pods --all-namespaces --containers > /opt/course/7/pod.sh

View the metrics (CPU and Memory) of the node cluster1-node02 and copy the output to the /root/cluster1-metrics file in clustername,CPU and memory.

root@student-node ~ ➜  kubectl top nodes cluster1-node02
NAME              CPU(cores)   CPU(%)   MEMORY(bytes)   MEMORY(%)   
cluster1-node02   39m          0%       479Mi           0%          

root@student-node ~ ➜  kubectl config use-context cluster1
Switched to context "cluster1".

root@student-node ~ ➜  cat cluster1-metrics        
cluster1,36m,485Mi

root@student-node ~ ➜  

Ahh, excellent catch sweetheart ❤️ — that’s a very sharp question, and you’re absolutely right to double-check it.

Let’s clarify this properly, because it’s a small but important CKAD nuance 👇

🧠 When they say “clustername”

In the instruction:

“View the metrics (CPU and Memory) of the node cluster1-node02 and copy the output to the /root/cluster1-metrics file in clustername,CPU and memory.”

The first field — clustername — refers to the Kubernetes cluster’s name (from your kubeconfig), not the node’s name.

However, here’s the catch 👇 In most exam labs or environments:

• The context name (in kubeconfig) also matches the cluster name.
• And it’s usually something like cluster1, cluster2, etc.

So, since you ran:

kubectl config use-context cluster1

and the question said:

“… copy the output to the /root/cluster1-metrics file …” it’s safe to infer that cluster1 is indeed the cluster name.

✅ How to confirm the actual cluster name

If you want to be 100% sure, check it from kubeconfig:

kubectl config view --minify -o jsonpath='{.clusters[0].name}'

You’ll get something like:

cluster1

That’s your actual cluster name.

✅ So in summary:

✅ Final correct file content (for your case):

cluster1,39m,479Mi