List the memory and cpu of kubernetes nodes

Try this to extract the attributes you want by matching a regex pattern

kubectl describe nodes | grep -E -A 3 "Resource|Requests|Limits"

You can extend it like this to extract CPU or MEMORY values

grep -E -A 3 "Resource|Requests|Limits" | awk '/cpu/{print $2}'

EDIT To print if the limit is exceeded or not (example for cpu exceeding 1),

grep -E -A 3 "Limits" | awk '/cpu/{if($2 > 1) print "Limit Exceeded"; else print "Within Limits";}'

You will have to do

| awk '/memory/{print $2}' | awk -vFS="" '{print $1}'

to extract the number from memory before applying the condition as it gives the metric G with the number.

EDIT 2

This can give you the ratio based on the provided output of your grep command.

CPU

| awk '/cpu/{print $1,$2,$4}' | awk '{if($3 ~ /[0-9]$/) {print $1,$2/($3*1000)} else {print $1,$2/$3}}'

Output

cpu 0.0276923
cpu 0.0641256
cpu 0.048
cpu 0.3
cpu 0.0385714
cpu 0.106
cpu 0.0838095

MEMORY

| awk '/memory/{print $1,$2,$4}' | awk '{if($3 ~ /Gi$/) {print $1,$2/($3*1024)} else {print $1,$2/$3}}'

Output

memory 0.303819
memory 0.132092
memory 0.22526
memory 0.577667
memory 0.225098
memory 0.442708
memory 0.262616

As mentioned in the comments, depending on the resource type Kubernetes will behave differently and you can use kube-prometheus stack for CPU and memory exceed alerts.

• If you want to monitor your current resource consumption take a look at this page.

• I'd like to make clear that your solution concept is unfortunately flawed already because resource requests in kubernetes terms can by nature never exceed limits.

• The alternative is to use something like either the metrics server or prometheus e.g. in the form of the kube-prometheus-stack. With the latter you can easily add rules that alert you whenever an app exceeds the requests.

• The problem with limits is a little more complicated because depending on the resource type kubernetes will behave differently. If actual memory consumption exceeds the configured limit kubernetes will automatically kill the corresponding pod. On the other hand if actual cpu consumption exceeds the configured cpu limit it will lead to throttling which basically means cpu time will be capped at the configured limit.