Kubernetes: Need simple kubectl command to see cluster resource usage

Something along the lines of (2) seems reasonable, though the UX folks would know better than me.

(3) seems vaguely related to #15743 but I'm not sure they're close enough to combine.

In addition to the case above, it would be nice to see what resource utilization we're getting.

kubectl utilization requests might show (maybe kubectl util or kubectl usage are better/shorter):

cores: 4.455/5 cores (89%)
memory: 20.1/30 GiB (67%)
...

In this example, the aggregate container requests are 4.455 cores and 20.1 GiB and there are 5 cores and 30GiB total in the cluster.

There is:

$ kubectl top nodes
NAME                    CPU(cores)   CPU%      MEMORY(bytes)   MEMORY%   
cluster1-k8s-master-1   312m         15%       1362Mi          68%       
cluster1-k8s-node-1     124m         12%       233Mi           11% 

I use below command to get a quick view for the resource usage. It is the simplest way I found.

kubectl describe nodes

If there was a way to "format" the output of kubectl describe nodes, I wouldn't mind scripting my way to summarize all node's resource requests/limits.

here is my hack kubectl describe nodes | grep -A 2 -e "^\\s*CPU Requests"

@from-nibly thanks, just what i was looking for

Yup, this is mine:

$ cat bin/node-resources.sh 
#!/bin/bash
set -euo pipefail

echo -e "Iterating...\n"

nodes=$(kubectl get node --no-headers -o custom-columns=NAME:.metadata.name)

for node in $nodes; do
  echo "Node: $node"
  kubectl describe node "$node" | sed '1,/Non-terminated Pods/d'
  echo
done

@goltermann There are no sig labels on this issue. Please add a sig label by:
(1) mentioning a sig: @kubernetes/sig-<team-name>-misc
(2) specifying the label manually: /sig <label>

_Note: method (1) will trigger a notification to the team. You can find the team list here._

@kubernetes/sig-cli-misc

You can use the below command to find the percentage cpu utlisation of your nodes

alias util='kubectl get nodes | grep node | awk '\''{print $1}'\'' | xargs -I {} sh -c '\''echo   {} ; kubectl describe node {} | grep Allocated -A 5 | grep -ve Event -ve Allocated -ve percent -ve -- ; echo '\'''

Note: 4000m cores is the total cores in one node
alias cpualloc="util | grep % | awk '{print \$1}' | awk '{ sum += \$1 } END { if (NR > 0) { result=(sum**4000); printf result/NR \"%\n\" } }'"

$ cpualloc
3.89358%

Note: 1600MB is the total cores in one node
alias memalloc='util | grep % | awk '\''{print $3}'\'' | awk '\''{ sum += $1 } END { if (NR > 0) { result=(sum*100)/(NR*1600); printf result/NR "%\n" } }'\'''

$ memalloc
24.6832%

@tomfotherby alias util='kubectl get nodes | grep node | awk '\''{print $1}'\'' | xargs -I {} sh -c '\''echo {} ; kubectl describe node {} | grep Allocated -A 5 | grep -ve Event -ve Allocated -ve percent -ve -- ; echo '\'''

@alok87 - Thanks for your aliases. In my case, this is what worked for me given that we use bash and m3.large instance types (2 cpu , 7.5G memory).

alias util='kubectl get nodes --no-headers | awk '\''{print $1}'\'' | xargs -I {} sh -c '\''echo {} ; kubectl describe node {} | grep Allocated -A 5 | grep -ve Event -ve Allocated -ve percent -ve -- ; echo '\'''

# Get CPU request total (we x20 because because each m3.large has 2 vcpus (2000m) )
alias cpualloc='util | grep % | awk '\''{print $1}'\'' | awk '\''{ sum += $1 } END { if (NR > 0) { print sum/(NR*20), "%\n" } }'\'''

# Get mem request total (we x75 because because each m3.large has 7.5G ram )
alias memalloc='util | grep % | awk '\''{print $5}'\'' | awk '\''{ sum += $1 } END { if (NR > 0) { print sum/(NR*75), "%\n" } }'\'''

$util
ip-10-56-0-178.ec2.internal
  CPU Requests  CPU Limits  Memory Requests Memory Limits
  960m (48%)    2700m (135%)    630Mi (8%)  2034Mi (27%)

ip-10-56-0-22.ec2.internal
  CPU Requests  CPU Limits  Memory Requests Memory Limits
  920m (46%)    1400m (70%) 560Mi (7%)  550Mi (7%)

ip-10-56-0-56.ec2.internal
  CPU Requests  CPU Limits  Memory Requests Memory Limits
  1160m (57%)   2800m (140%)    972Mi (13%) 3976Mi (53%)

ip-10-56-0-99.ec2.internal
  CPU Requests  CPU Limits  Memory Requests Memory Limits
  804m (40%)    794m (39%)  824Mi (11%) 1300Mi (17%)

cpualloc 
48.05 %

$ memalloc 
9.95333 %

https://github.com/kubernetes/kubernetes/issues/17512#issuecomment-267992922 kubectl top shows usage, not allocation. Allocation is what causes the insufficient CPU problem. There's a ton of confusion in this issue about the difference.

AFAICT, there's no easy way to get a report of node CPU allocation by pod, since requests are per container in the spec. And even then, it's difficult since .spec.containers[*].requests may or may not have the limits/requests fields (in my experience)

/cc @misterikkit

Getting in on this shell scripting party. I have an older cluster running the CA with scale down disabled. I wrote this script to determine roughly how much I can scale down the cluster when it starts to bump up on its AWS route limits:

#!/bin/bash

set -e

KUBECTL="kubectl"
NODES=$($KUBECTL get nodes --no-headers -o custom-columns=NAME:.metadata.name)

function usage() {
    local node_count=0
    local total_percent_cpu=0
    local total_percent_mem=0
    local readonly nodes=$@

    for n in $nodes; do
        local requests=$($KUBECTL describe node $n | grep -A2 -E "^\\s*CPU Requests" | tail -n1)
        local percent_cpu=$(echo $requests | awk -F "[()%]" '{print $2}')
        local percent_mem=$(echo $requests | awk -F "[()%]" '{print $8}')
        echo "$n: ${percent_cpu}% CPU, ${percent_mem}% memory"

        node_count=$((node_count + 1))
        total_percent_cpu=$((total_percent_cpu + percent_cpu))
        total_percent_mem=$((total_percent_mem + percent_mem))
    done

    local readonly avg_percent_cpu=$((total_percent_cpu / node_count))
    local readonly avg_percent_mem=$((total_percent_mem / node_count))

    echo "Average usage: ${avg_percent_cpu}% CPU, ${avg_percent_mem}% memory."
}

usage $NODES

Produces output like:

ip-REDACTED.us-west-2.compute.internal: 38% CPU, 9% memory
...many redacted lines...
ip-REDACTED.us-west-2.compute.internal: 41% CPU, 8% memory
ip-REDACTED.us-west-2.compute.internal: 61% CPU, 7% memory
Average usage: 45% CPU, 15% memory.

There is also pod option in top command:

kubectl top pod

@ylogx https://github.com/kubernetes/kubernetes/issues/17512#issuecomment-326089708

My way to obtain the allocation, cluster-wide:

$ kubectl get po --all-namespaces -o=jsonpath="{range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}{range .spec.containers[*]}  {.name}:{.resources.requests.cpu}{'\n'}{end}{'\n'}{end}"

It produces something like:

kube-system:heapster-v1.5.0-dc8df7cc9-7fqx6
  heapster:88m
  heapster-nanny:50m
kube-system:kube-dns-6cdf767cb8-cjjdr
  kubedns:100m
  dnsmasq:150m
  sidecar:10m
  prometheus-to-sd:
kube-system:kube-dns-6cdf767cb8-pnx2g
  kubedns:100m
  dnsmasq:150m
  sidecar:10m
  prometheus-to-sd:
kube-system:kube-dns-autoscaler-69c5cbdcdd-wwjtg
  autoscaler:20m
kube-system:kube-proxy-gke-cluster1-default-pool-cd7058d6-3tt9
  kube-proxy:100m
kube-system:kube-proxy-gke-cluster1-preempt-pool-57d7ff41-jplf
  kube-proxy:100m
kube-system:kubernetes-dashboard-7b9c4bf75c-f7zrl
  kubernetes-dashboard:50m
kube-system:l7-default-backend-57856c5f55-68s5g
  default-http-backend:10m
kube-system:metrics-server-v0.2.0-86585d9749-kkrzl
  metrics-server:48m
  metrics-server-nanny:5m
kube-system:tiller-deploy-7794bfb756-8kxh5
  tiller:10m

This is weird. I want to know when I'm at or nearing allocation capacity. It seems a pretty basic function of a cluster. Whether it's a statistic that shows a high % or textual error... how do other people know this? Just always use autoscaling on a cloud platform?

I authored https://github.com/dpetzold/kube-resource-explorer/ to address #3. Here is some sample output:

$ ./resource-explorer -namespace kube-system -reverse -sort MemReq
Namespace    Name                                               CpuReq  CpuReq%  CpuLimit  CpuLimit%  MemReq    MemReq%  MemLimit  MemLimit%
---------    ----                                               ------  -------  --------  ---------  ------    -------  --------  ---------
kube-system  event-exporter-v0.1.7-5c4d9556cf-kf4tf             0       0%       0         0%         0         0%       0         0%
kube-system  kube-proxy-gke-project-default-pool-175a4a05-mshh  100m    10%      0         0%         0         0%       0         0%
kube-system  kube-proxy-gke-project-default-pool-175a4a05-bv59  100m    10%      0         0%         0         0%       0         0%
kube-system  kube-proxy-gke-project-default-pool-175a4a05-ntfw  100m    10%      0         0%         0         0%       0         0%
kube-system  kube-dns-autoscaler-244676396-xzgs4                20m     2%       0         0%         10Mi      0%       0         0%
kube-system  l7-default-backend-1044750973-kqh98                10m     1%       10m       1%         20Mi      0%       20Mi      0%
kube-system  kubernetes-dashboard-768854d6dc-jh292              100m    10%      100m      10%        100Mi     3%       300Mi     11%
kube-system  kube-dns-323615064-8nxfl                           260m    27%      0         0%         110Mi     4%       170Mi     6%
kube-system  fluentd-gcp-v2.0.9-4qkwk                           100m    10%      0         0%         200Mi     7%       300Mi     11%
kube-system  fluentd-gcp-v2.0.9-jmtpw                           100m    10%      0         0%         200Mi     7%       300Mi     11%
kube-system  fluentd-gcp-v2.0.9-tw9vk                           100m    10%      0         0%         200Mi     7%       300Mi     11%
kube-system  heapster-v1.4.3-74b5bd94bb-fz8hd                   138m    14%      138m      14%        301856Ki  11%      301856Ki  11%

@shtouff

root@debian9:~# kubectl get po -n chenkunning-84 -o=jsonpath="{range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}{range .spec.containers[*]}  {.name}:{.resources.requests.cpu}{'\n'}{end}{'\n'}{end}"
error: error parsing jsonpath {range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}{range .spec.containers[*]}  {.name}:{.resources.requests.cpu}{'\n'}{end}{'\n'}{end}, unrecognized character in action: U+0027 '''
root@debian9:~# kubectl version
Client Version: version.Info{Major:"1", Minor:"6+", GitVersion:"v1.6.7-beta.0+$Format:%h$", GitCommit:"bb053ff0cb25a043e828d62394ed626fda2719a1", GitTreeState:"dirty", BuildDate:"2017-08-26T09:34:19Z", GoVersion:"go1.8", Compiler:"gc", Platform:"linux/amd64"}
Server Version: version.Info{Major:"1", Minor:"6+", GitVersion:"v1.6.7-beta.0+$Format:84c3ae0384658cd40c1d1e637f5faa98cf6a965c$", GitCommit:"3af2004eebf3cbd8d7f24b0ecd23fe4afb889163", GitTreeState:"clean", BuildDate:"2018-04-04T08:40:48Z", GoVersion:"go1.8.1", Compiler:"gc", Platform:"linux/amd64"}

@harryge00: U+0027 is a curly quote, probably a copy-paste problem

@nfirvine Thanks! I have solved problem by using:

kubectl get pods -n my-ns -o=jsonpath='{range .items[*]}{.metadata.name}{"\t"}{.spec.containers[0].resources.limits.cpu} {"\n"}{end}' |awk '{sum+=$2 ; print $0} END{print "sum=",sum}'

It works for namespaces whose pods only containing 1 container each.

@xmik Hey, I'm using k8 1.7 and running hepaster. When I run $ kubectl top nodes --heapster-namespace=kube-system, it shows me "error: metrics not available yet". Any clue for tackling the error?

@abushoeb:

1. I don't think kubectl top supports flag: --heapster-namespace. Edit: this flag is supported, you were right: https://github.com/kubernetes/kubernetes/issues/44540#issuecomment-362882035 .
2. If you see "error: metrics not available yet", then you should check heapster deployment. What its logs say? Is the heapster service ok, endpoints are not <none>? Check the latter with a command like: kubectl -n kube-system describe svc/heapster

@xmik you are right, the heapster wasn't configured properly. Thanks a lot. It's working now. Do you know if there is a way to get real-time GPU usage information? This top command only gives CPU and Memory usage.

I don't know that. :(

@abushoeb I am getting the same error "error: metrics not available yet" . How did you fix it?

@avgKol check you heapster deployment first. In my case, it was not deployed properly. One way to check it is to access metrics via CURL command like curl -L http://heapster-pod-ip:heapster-service-port/api/v1/model/metrics/. If it doesn't show metrics then check the heapster pod and logs. The hepster metrics can be accessed via a web browser too like this.

If anybody is interested, I created a tool to generate static HTML for Kubernetes resource usage (and costs): https://github.com/hjacobs/kube-resource-report

@hjacobs I would like to use that tool but not a fan of installing/using python packages. Mind packaging it up as a docker image?

@tonglil the project is pretty early, but my plan is to have an out-of-the-box ready Docker image incl. webserver which you can just do kubectl apply -f .. with.

Here is what worked for me:

kubectl get nodes -o=jsonpath="{range .items[*]}{.metadata.name}{'\t'}{.status.allocatable.memory}{'\t'}{.status.allocatable.cpu}{'\n'}{end}"

It shows output as:

ip-192-168-101-177.us-west-2.compute.internal   251643680Ki 32
ip-192-168-196-254.us-west-2.compute.internal   251643680Ki 32

@tonglil a Docker image is now available: https://github.com/hjacobs/kube-resource-report

Issues go stale after 90d of inactivity.
Mark the issue as fresh with /remove-lifecycle stale.
Stale issues rot after an additional 30d of inactivity and eventually close.

If this issue is safe to close now please do so with /close.

Send feedback to sig-testing, kubernetes/test-infra and/or fejta.
/lifecycle stale

/remove-lifecycle stale

Every month or so, my Googling leads me back to this issue. There are ways of getting the statistics I need with long jq strings, or with Grafana dashboards with a bunch of calculations... but it would be _so_ nice if there were a command like:

# kubectl utilization cluster
cores: 19.255/24 cores (80%)
memory: 16.4/24 GiB (68%)

# kubectl utilization [node name]
cores: 3.125/4 cores (78%)
memory: 2.1/4 GiB (52%)

(similar to what @chrishiestand mentioned way earlier in the thread).

I am often building and destroying a few dozen test clusters per week, and I'd rather not have to build automation or add in some shell aliases to be able to just see "if I put this many servers out there, and toss these apps on them, what is my overall utilization/pressure".

Especially for smaller / more esoteric clusters, I don't want to set up autoscale-to-the-moon (usually for money reasons), but do need to know if I have enough overhead to handle minor pod autoscaling events.

One additional request -- I'd like to be able to see summed resource usage by namespace (at a minimum; by Deployment/label would also be useful), so I can focus my resource-trimming efforts by figuring out which namespaces are worth concentrating on.

I made a small plugin kubectl-view-utilization, that provides functionality @geerlingguy described. Installation via krew plugin manager is available. This is implemented in BASH and it needs awk and bc.
With kubectl plugin framework this could be completely abstracted away from core tools.

I am glad others were also facing this challenge. I created Kube Eagle (a prometheus exporter) which helped me gaining a better overview of cluster resources and ultimately let me better utilize the available hardware resources:

https://github.com/google-cloud-tools/kube-eagle

This is a python script to get the actual node utilization in table format
https://github.com/amelbakry/kube-node-utilization

Kubernetes Node Utilization..........
+------------------------------------------------+--------+--------+
| NodeName | CPU | Memory |
+------------------------------------------------+--------+--------+
| ip-176-35-32-139.eu-central-1.compute.internal | 13.49% | 60.87% |
| ip-176-35-26-21.eu-central-1.compute.internal | 5.89% | 15.10% |
| ip-176-35-9-122.eu-central-1.compute.internal | 8.08% | 65.51% |
| ip-176-35-22-243.eu-central-1.compute.internal | 6.29% | 19.28% |
+------------------------------------------------+--------+--------+

For me at least @amelbakry it's cluster-level utilisation that's important: "do I need to add more machines?" / "should I remove some machines?" / "should I expect the cluster to scale up soon?" ..

What about ephemeral storage usage? Any ideas how to get it from all pods?

And to be useful, my hints:

kubectl get pods -o json -n kube-system | jq -r '.items[] | .metadata.name + " \n Req. RAM: " + .spec.containers[].resources.requests.memory + " \n Lim. RAM: " + .spec.containers[].resources.limits.memory + " \n Req. CPU: " + .spec.containers[].resources.requests.cpu + " \n Lim. CPU: " + .spec.containers[].resources.limits.cpu + " \n Req. Eph. DISK: " + .spec.containers[].resources.requests["ephemeral-storage"] + " \n Lim. Eph. DISK: " + .spec.containers[].resources.limits["ephemeral-storage"] + "\n"'
...
kube-proxy-xlmjt
 Req. RAM: 32Mi
 Lim. RAM: 256Mi
 Req. CPU: 100m
 Lim. CPU:
 Req. Eph. DISK: 100Mi
 Lim. Eph. DISK: 512Mi
...

echo "\nRAM Requests TOTAL:" && kubectl describe namespace kube-system | grep 'requests.memory' && echo "\nRAM Requests:\n" && kubectl get pods -o json -n kube-system | jq -r '.items[] | .spec.containers[].resources.requests.memory + " | " + .metadata.name'

echo "\nRAM Limits TOTAL:" && kubectl describe namespace kube-system | grep 'limits.memory' &&  echo "\nRAM Limits:\n" && kubectl get pods -o json -n kube-system | jq -r '.items[] | .spec.containers[].resources.limits.memory + " | " + .metadata.name'

echo "\nCPU Requests TOTAL:" && kubectl describe namespace kube-system | grep 'requests.cpu' &&  echo "\nCPU Requests:\n" && kubectl get pods -o json -n kube-system | jq -r '.items[] | .spec.containers[].resources.requests.cpu + " | " + .metadata.name'

echo "\nCPU Limits TOTAL:" && kubectl describe namespace kube-system | grep 'limits.cpu' &&  echo "\nCPU Limits:\n" && kubectl get pods -o json -n kube-system | jq -r '.items[] | .spec.containers[].resources.limits.cpu + " | " + .metadata.name'

echo "\nEph. DISK Requests TOTAL:" && kubectl describe namespace kube-system | grep 'requests.ephemeral-storage' && echo "\nEph. DISK Requests:\n" && kubectl get pods -o json -n kube-system | jq -r '.items[] | .spec.containers[].resources.requests["ephemeral-storage"] + " | " + .metadata.name'

echo "\nEph. DISK Limits TOTAL:" && kubectl describe namespace kube-system | grep 'limits.ephemeral-storage' && echo "\nEph. DISK Limits:\n" && kubectl get pods -o json -n kube-system | jq -r '.items[] | .spec.containers[].resources.limits["ephemeral-storage"] + " | " + .metadata.name'

RAM Requests TOTAL:
 requests.memory               3504Mi   16Gi

RAM Requests:

64Mi | aws-alb-ingress-controller-6b569b448c-jzj6f
...

@kivagant-ba you can try this snipt to get pod metrics per node, you can get all nodes like
https://github.com/amelbakry/kube-node-utilization

def get_pod_metrics_per_node(node):
pod_metrics = "/api/v1/pods?fieldSelector=spec.nodeName%3D" + node
response = api_client.call_api(pod_metrics,
'GET', auth_settings=['BearerToken'],
response_type='json', _preload_content=False)

response = json.loads(response[0].data.decode('utf-8'))

return response

@kierenj I think the cluster-autoscaler component based on which cloud kubernetes is running should handle the capacity. not sure if this is your question.

Issues go stale after 90d of inactivity.
Mark the issue as fresh with /remove-lifecycle stale.
Stale issues rot after an additional 30d of inactivity and eventually close.

If this issue is safe to close now please do so with /close.

Send feedback to sig-testing, kubernetes/test-infra and/or fejta.
/lifecycle stale

/remove-lifecycle stale

I, like many others, keep coming back here - for years - to get the hack we need to manage the clusters via CLI (e.g. AWS ASGs)

@etopeter Thank you for such a cool CLI plugin. Love the simplicity of it. Any advice on how to better understand the numbers and their exact meaning?

If anyone can find use of it here is a script that will dump current limits of pods.

kubectl get pods --all-namespaces -o=jsonpath="{range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}\ {'.spec.nodeName -'} {.spec.nodeName}{'\n'}\ {range .spec.containers[*]}\ {'requests.cpu -'} {.resources.requests.cpu}{'\n'}\ {'limits.cpu -'} {.resources.limits.cpu}{'\n'}\ {'requests.memory -'} {.resources.requests.memory}{'\n'}\ {'limits.memory -'} {.resources.limits.memory}{'\n'}\ {'\n'}{end}\ {'\n'}{end}"

Example output
...
kube-system:addon-http-application-routing-nginx-ingress-controller-6bq49l7
.spec.nodeName - aks-agentpool-84550961-0
requests.cpu -
limits.cpu -
requests.memory -
limits.memory -

kube-system:coredns-696c4d987c-pjht8
.spec.nodeName - aks-agentpool-84550961-0
requests.cpu - 100m
limits.cpu -
requests.memory - 70Mi
limits.memory - 170Mi

kube-system:coredns-696c4d987c-rtkl6
.spec.nodeName - aks-agentpool-84550961-2
requests.cpu - 100m
limits.cpu -
requests.memory - 70Mi
limits.memory - 170Mi

kube-system:coredns-696c4d987c-zgcbp
.spec.nodeName - aks-agentpool-84550961-1
requests.cpu - 100m
limits.cpu -
requests.memory - 70Mi
limits.memory - 170Mi

kube-system:coredns-autoscaler-657d77ffbf-7t72x
.spec.nodeName - aks-agentpool-84550961-2
requests.cpu - 20m
limits.cpu -
requests.memory - 10Mi
limits.memory -

kube-system:coredns-autoscaler-657d77ffbf-zrp6m
.spec.nodeName - aks-agentpool-84550961-0
requests.cpu - 20m
limits.cpu -
requests.memory - 10Mi
limits.memory -

kube-system:kube-proxy-57nw5
.spec.nodeName - aks-agentpool-84550961-1
requests.cpu - 100m
limits.cpu -
requests.memory -
limits.memory -
...

@Spaceman1861 could you show an example outout?

@eduncan911 done

I find it easier to read the output in table format, like this (this shows requests instead of limits):

kubectl get pods -o custom-columns=NAME:.metadata.name,"CPU(cores)":.spec.containers[*].resources.requests.cpu,"MEMORY(bytes)":.spec.containers[*].resources.requests.memory --all-namespaces

Sample output:

NAME                                CPU(cores)      MEMORY(bytes)
pod1                                100m            128Mi
pod2                                100m            128Mi,128Mi

@lentzi90 just FYI: you can show similar custom columns in Kubernetes Web View ("kubectl for the web"), demo: https://kube-web-view.demo.j-serv.de/clusters/local/namespaces/default/pods?join=metrics;customcols=CPU+Requests=join(%27,%20%27,%20spec.containers[].resources.requests.cpu)%3BMemory+Requests=join(%27,%20%27,%20spec.containers[].resources.requests.memory)

Docs on custom columns: https://kube-web-view.readthedocs.io/en/latest/features.html#listing-resources

Oooo shiny @hjacobs I like that.

This is a script (deployment-health.sh) to get the utilization of the pods in deployment based on the usage and configured limits
https://github.com/amelbakry/kubernetes-scripts

Inspired by the answers of @lentzi90 and @ylogx, I have created own big script which shows actual resource usage (kubectl top pods) and resource requests and limits:

join -a1 -a2 -o 0,1.2,1.3,2.2,2.3,2.4,2.5, -e '<none>' <(kubectl top pods) <(kubectl get pods -o custom-columns=NAME:.metadata.name,"CPU_REQ(cores)":.spec.containers[*].resources.requests.cpu,"MEMORY_REQ(bytes)":.spec.containers[*].resources.requests.memory,"CPU_LIM(cores)":.spec.containers[*].resources.limits.cpu,"MEMORY_LIM(bytes)":.spec.containers[*].resources.limits.memory) | column -t -s' ' 

output example:

NAME                                                             CPU(cores)  MEMORY(bytes)  CPU_REQ(cores)  MEMORY_REQ(bytes)  CPU_LIM(cores)  MEMORY_LIM(bytes)
xxxxx-847dbbc4c-c6twt                                            20m         110Mi          50m             150Mi              150m            250Mi
xxx-service-7b6b9558fc-9cq5b                                     19m         1304Mi         1               <none>             1               <none>
xxxxxxxxxxxxxxx-hook-5d585b449b-zfxmh                            0m          46Mi           200m            155M               200m            155M

Here is the alias for you to just use kstats in your terminal:

alias kstats='join -a1 -a2 -o 0,1.2,1.3,2.2,2.3,2.4,2.5, -e '"'"'<none>'"'"' <(kubectl top pods) <(kubectl get pods -o custom-columns=NAME:.metadata.name,"CPU_REQ(cores)":.spec.containers[*].resources.requests.cpu,"MEMORY_REQ(bytes)":.spec.containers[*].resources.requests.memory,"CPU_LIM(cores)":.spec.containers[*].resources.limits.cpu,"MEMORY_LIM(bytes)":.spec.containers[*].resources.limits.memory) | column -t -s'"'"' '"'" 

P.S. I've tested scripts only on my mac, for linux and windows it may require some changes

This is a script (deployment-health.sh) to get the utilization of the pods in deployment based on the usage and configured limits
https://github.com/amelbakry/kubernetes-scripts

@amelbakry I am getting the following error trying to execute it on a Mac:

Failed to execute process './deployment-health.sh'. Reason:
exec: Exec format error
The file './deployment-health.sh' is marked as an executable but could not be run by the operating system.

Woops,
"#!" needs to be the very first line. Instead try "bash
./deployment-health.sh" to work around the issue.

/charles
PS. PR opened to fix the issue

On Wed, Sep 25, 2019 at 10:19 AM Dmitri Moore notifications@github.com
wrote:

This is a script (deployment-health.sh) to get the utilization of the pods
in deployment based on the usage and configured limits
https://github.com/amelbakry/kubernetes-scripts

@amelbakry https://github.com/amelbakry I am getting the following
error trying to execute it on a Mac:

Failed to execute process './deployment-health.sh'. Reason:
exec: Exec format error
The file './deployment-health.sh' is marked as an executable but could not be run by the operating system.

—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/kubernetes/kubernetes/issues/17512?email_source=notifications&email_token=AACA3TODQEUPWK3V3UY3SF3QLOMSFA5CNFSM4BUXCUG2YY3PNVWWK3TUL52HS4DFVREXG43VMVBW63LNMVXHJKTDN5WW2ZLOORPWSZGOD7SVHRQ#issuecomment-535122886,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AACA3TOPOBIWXFX2DAOT6JDQLOMSFANCNFSM4BUXCUGQ
.

@cgthayer You might want to apply that PR fix globally. Also, when I ran the scripts on MacOs Mojave, a bunch of errors showed up, including EU specific zone names which I don't use. Looks like these scripts have been written for a specific project.

Here's a modified version of the join ex. which does totals of columns as well.

oc_ns_pod_usage () {
    # show pod usage for cpu/mem
    ns="$1"
    usage_chk3 "$ns" || return 1
    printf "$ns\n"
    separator=$(printf '=%.0s' {1..50})
    printf "$separator\n"
    output=$(join -a1 -a2 -o 0,1.2,1.3,2.2,2.3,2.4,2.5, -e '<none>' \
        <(kubectl top pods -n $ns) \
        <(kubectl get -n $ns pods -o custom-columns=NAME:.metadata.name,"CPU_REQ(cores)":.spec.containers[*].resources.requests.cpu,"MEMORY_REQ(bytes)":.spec.containers[*].resources.requests.memory,"CPU_LIM(cores)":.spec.containers[*].resources.limits.cpu,"MEMORY_LIM(bytes)":.spec.containers[*].resources.limits.memory))
    totals=$(printf "%s" "$output" | awk '{s+=$2; t+=$3; u+=$4; v+=$5; w+=$6; x+=$7} END {print s" "t" "u" "v" "w" "x}')
    printf "%s\n%s\nTotals: %s\n" "$output" "$separator" "$totals" | column -t -s' '
    printf "$separator\n"
}

Example

$ oc_ns_pod_usage ls-indexer
ls-indexer
==================================================
NAME                                                CPU(cores)  MEMORY(bytes)  CPU_REQ(cores)  MEMORY_REQ(bytes)  CPU_LIM(cores)  MEMORY_LIM(bytes)
ls-indexer-f5-7cd5859997-qsfrp                      15m         741Mi          1               1000Mi             2               2000Mi
ls-indexer-f5-7cd5859997-sclvg                      15m         735Mi          1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-4b7j2                 92m         1103Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-5xj5l                 88m         1124Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-6vvl2                 92m         1132Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-85f66                 85m         1151Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-924jz                 96m         1124Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-g6gx8                 119m        1119Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-hkhnt                 52m         819Mi          1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-hrsrs                 51m         1122Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-j4qxm                 53m         885Mi          1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-lxlrb                 83m         1215Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-mw6rt                 86m         1131Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-pbdf8                 95m         1115Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-qk9bm                 91m         1141Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-sdv9r                 54m         1194Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-t67v6                 75m         1234Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-tkxs2                 88m         1364Mi         1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-v6jl2                 53m         747Mi          1               1000Mi             2               2000Mi
ls-indexer-filebeat-7858f56c9-wkqr7                 53m         838Mi          1               1000Mi             2               2000Mi
ls-indexer-metricbeat-74d89d7d85-jp8qc              190m        1191Mi         1               1000Mi             2               2000Mi
ls-indexer-metricbeat-74d89d7d85-jv4bv              192m        1162Mi         1               1000Mi             2               2000Mi
ls-indexer-metricbeat-74d89d7d85-k4dcd              194m        1144Mi         1               1000Mi             2               2000Mi
ls-indexer-metricbeat-74d89d7d85-n46tz              192m        1155Mi         1               1000Mi             2               2000Mi
ls-indexer-packetbeat-db98f6fdf-8x446               35m         1198Mi         1               1000Mi             2               2000Mi
ls-indexer-packetbeat-db98f6fdf-gmxxd               22m         1203Mi         1               1000Mi             2               2000Mi
ls-indexer-syslog-5466bc4d4f-gzxw8                  27m         1125Mi         1               1000Mi             2               2000Mi
ls-indexer-syslog-5466bc4d4f-zh7st                  29m         1153Mi         1               1000Mi             2               2000Mi
==================================================
Totals:                                             2317        30365          28              28000              56              56000
==================================================

And what is usage_chk3?

I would like to also share my tools ;-) kubectl-view-allocations: kubectl plugin to list allocations (cpu, memory, gpu,... X requested, limit, allocatable,...)., request are welcome.

I made it because I would like to provide to my (internal) users a way to see "who allocates what". By default every resources are displayed, but in the following sample I only request resource with "gpu" in name.

> kubectl-view-allocations -r gpu

 Resource                                   Requested  %Requested  Limit  %Limit  Allocatable  Free
  nvidia.com/gpu                                    7         58%      7     58%           12     5
  ├─ node-gpu1                                      1         50%      1     50%            2     1
  │  └─ xxxx-784dd998f4-zt9dh                       1                  1
  ├─ node-gpu2                                      0          0%      0      0%            2     2
  ├─ node-gpu3                                      0          0%      0      0%            2     2
  ├─ node-gpu4                                      1         50%      1     50%            2     1
  │  └─ aaaa-1571819245-5ql82                       1                  1
  ├─ node-gpu5                                      2        100%      2    100%            2     0
  │  ├─ bbbb-1571738839-dfkhn                       1                  1
  │  └─ bbbb-1571738888-52c4w                       1                  1
  └─ node-gpu6                                      2        100%      2    100%            2     0
     ├─ bbbb-1571738688-vlxng                       1                  1
     └─ cccc-1571745684-7k6bn                       1                  1

coming version(s):

• will allow to hide (node, pod) level or to choose how to group, (eg to provide an overview with only resources)
• installation via curl, krew, brew, ... (currently binary are available under the releases section of github)

Thanks to kubectl-view-utilization for the inspiration, but adding support to other resources was to many copy/paste or hard to do for me in bash (for a generic way).

here is my hack kubectl describe nodes | grep -A 2 -e "^\\s*CPU Requests"

This doesn't work anymore :(

Give kubectl describe node | grep -A5 "Allocated" a try

This is currently the 4th highest requested issue by thumbs up, but still is priority/backlog.

I'd be happy to take a stab at this if someone could point me in the right direction or if we could finalize a proposal. I think the UX of @davidB's tool is awesome, but this really belongs in the core kubectl.

Using the following comands: kubectl top nodes & kubectl describe node we do not get consistent results

For example with the first one the CPU(cores) are 1064m but this result cannot be fetched with the second one(1480m):

kubectl top nodes
NAME                                                CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%
abcd-p174e23ea5qa4g279446c803f82-abc-node-0         1064m        53%    6783Mi          88%

kubectl describe node abcd-p174e23ea5qa4g279446c803f82-abc-node-0
...
  Resource  Requests          Limits
  --------  --------          ------
  cpu       1480m (74%)       1300m (65%)
  memory    2981486848 (37%)  1588314624 (19%)

Any idea about getting the CPU(cores) without using the kubectl top nodes ?

I would like to also share my tools ;-) kubectl-view-allocations: kubectl plugin to list allocations (cpu, memory, gpu,... X requested, limit, allocatable,...)., request are welcome.

I made it because I would like to provide to my (internal) users a way to see "who allocates what". By default every resources are displayed, but in the following sample I only request resource with "gpu" in name.

> kubectl-view-allocations -r gpu

 Resource                                   Requested  %Requested  Limit  %Limit  Allocatable  Free
  nvidia.com/gpu                                    7         58%      7     58%           12     5
  ├─ node-gpu1                                      1         50%      1     50%            2     1
  │  └─ xxxx-784dd998f4-zt9dh                       1                  1
  ├─ node-gpu2                                      0          0%      0      0%            2     2
  ├─ node-gpu3                                      0          0%      0      0%            2     2
  ├─ node-gpu4                                      1         50%      1     50%            2     1
  │  └─ aaaa-1571819245-5ql82                       1                  1
  ├─ node-gpu5                                      2        100%      2    100%            2     0
  │  ├─ bbbb-1571738839-dfkhn                       1                  1
  │  └─ bbbb-1571738888-52c4w                       1                  1
  └─ node-gpu6                                      2        100%      2    100%            2     0
     ├─ bbbb-1571738688-vlxng                       1                  1
     └─ cccc-1571745684-7k6bn                       1                  1

coming version(s):

* will allow to hide (node, pod) level or to choose how to group, (eg to provide an overview with only resources)

* installation via curl, krew, brew, ... (currently binary are available under the releases section of github)

Thanks to kubectl-view-utilization for the inspiration, but adding support to other resources was to many copy/paste or hard to do for me in bash (for a generic way).

Hello David it would be nice if you provide more compiled binary for new distributions. On Ubuntu 16.04 we get

kubectl-view-allocations: /lib/x86_64-linux-gnu/libc.so.6: version `GLIBC_2.25' not found (required by kubectl-view-allocations)

dpkg -l |grep glib

ii libglib2.0-0:amd64 2.48.2-0ubuntu4.4

@omerfsen can you try the new version kubectl-view-allocations and comment into the ticket version `GLIBC_2.25' not found #14 ?

My way to obtain the allocation, cluster-wide:

$ kubectl get po --all-namespaces -o=jsonpath="{range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}{range .spec.containers[*]}  {.name}:{.resources.requests.cpu}{'\n'}{end}{'\n'}{end}"

It produces something like:

kube-system:heapster-v1.5.0-dc8df7cc9-7fqx6
  heapster:88m
  heapster-nanny:50m
kube-system:kube-dns-6cdf767cb8-cjjdr
  kubedns:100m
  dnsmasq:150m
  sidecar:10m
  prometheus-to-sd:
kube-system:kube-dns-6cdf767cb8-pnx2g
  kubedns:100m
  dnsmasq:150m
  sidecar:10m
  prometheus-to-sd:
kube-system:kube-dns-autoscaler-69c5cbdcdd-wwjtg
  autoscaler:20m
kube-system:kube-proxy-gke-cluster1-default-pool-cd7058d6-3tt9
  kube-proxy:100m
kube-system:kube-proxy-gke-cluster1-preempt-pool-57d7ff41-jplf
  kube-proxy:100m
kube-system:kubernetes-dashboard-7b9c4bf75c-f7zrl
  kubernetes-dashboard:50m
kube-system:l7-default-backend-57856c5f55-68s5g
  default-http-backend:10m
kube-system:metrics-server-v0.2.0-86585d9749-kkrzl
  metrics-server:48m
  metrics-server-nanny:5m
kube-system:tiller-deploy-7794bfb756-8kxh5
  tiller:10m

by far the best answer here.

Inspired by the scripts above I created the following script to view the usage, requests and limits:

join -1 2 -2 2 -a 1 -a 2 -o "2.1 0 1.3 2.3 2.5 1.4 2.4 2.6" -e '<wait>' \
  <( kubectl top pods --all-namespaces | sort --key 2 -b ) \
  <( kubectl get pods --all-namespaces -o custom-columns=NAMESPACE:.metadata.namespace,NAME:.metadata.name,"CPU_REQ(cores)":.spec.containers[*].resources.requests.cpu,"MEMORY_REQ(bytes)":.spec.containers[*].resources.requests.memory,"CPU_LIM(cores)":.spec.containers[*].resources.limits.cpu,"MEMORY_LIM(bytes)":.spec.containers[*].resources.limits.memory | sort --key 2 -b ) \
  | column -t -s' '

Because the join shell script expects a sorted list, the scripts given above failed for me.

You see as a result the current usage from top and from the deployment the requests and the limits of (here) all namespaces:

NAMESPACE                 NAME                                                        CPU(cores)  CPU_REQ(cores)  CPU_LIM(cores)  MEMORY(bytes)  MEMORY_REQ(bytes)   MEMORY_LIM(bytes)
kube-system               aws-node-2jzxr                                              18m         10m             <none>          41Mi           <none>              <none>
kube-system               aws-node-5zn6w                                              <wait>      10m             <none>          <wait>         <none>              <none>
kube-system               aws-node-h8cc5                                              20m         10m             <none>          42Mi           <none>              <none>
kube-system               aws-node-h9n4f                                              0m          10m             <none>          0Mi            <none>              <none>
kube-system               aws-node-lz5fn                                              17m         10m             <none>          41Mi           <none>              <none>
kube-system               aws-node-tpmxr                                              20m         10m             <none>          39Mi           <none>              <none>
kube-system               aws-node-zbkkh                                              23m         10m             <none>          47Mi           <none>              <none>
cluster-autoscaler        cluster-autoscaler-aws-cluster-autoscaler-5db55fbcf8-mdzkd  1m          100m            500m            9Mi            300Mi               500Mi
cluster-autoscaler        cluster-autoscaler-aws-cluster-autoscaler-5db55fbcf8-q9xs8  39m         100m            500m            75Mi           300Mi               500Mi
kube-system               coredns-56b56b56cd-bb26t                                    6m          100m            <none>          11Mi           70Mi                170Mi
kube-system               coredns-56b56b56cd-nhp58                                    6m          100m            <none>          11Mi           70Mi                170Mi
kube-system               coredns-56b56b56cd-wrmxv                                    7m          100m            <none>          12Mi           70Mi                170Mi
gitlab-runner-l           gitlab-runner-l-gitlab-runner-6b8b85f87f-9knnx              3m          100m            200m            10Mi           128Mi               256Mi
gitlab-runner-m           gitlab-runner-m-gitlab-runner-6bfd5d6c84-t5nrd              7m          100m            200m            13Mi           128Mi               256Mi
gitlab-runner-mda         gitlab-runner-mda-gitlab-runner-59bb66c8dd-bd9xw            4m          100m            200m            17Mi           128Mi               256Mi
gitlab-runner-ops         gitlab-runner-ops-gitlab-runner-7c5b85dc97-zkb4c            3m          100m            200m            12Mi           128Mi               256Mi
gitlab-runner-pst         gitlab-runner-pst-gitlab-runner-6b8f9bf56b-sszlr            6m          100m            200m            20Mi           128Mi               256Mi
gitlab-runner-s           gitlab-runner-s-gitlab-runner-6bbccb9b7b-dmwgl              50m         100m            200m            27Mi           128Mi               512Mi
gitlab-runner-shared      gitlab-runner-shared-gitlab-runner-688d57477f-qgs2z         3m          <none>          <none>          15Mi           <none>              <none>
kube-system               kube-proxy-5b65t                                            15m         100m            <none>          19Mi           <none>              <none>
kube-system               kube-proxy-7qsgh                                            12m         100m            <none>          24Mi           <none>              <none>
kube-system               kube-proxy-gn2qg                                            13m         100m            <none>          23Mi           <none>              <none>
kube-system               kube-proxy-pz7fp                                            15m         100m            <none>          18Mi           <none>              <none>
kube-system               kube-proxy-vdjqt                                            15m         100m            <none>          23Mi           <none>              <none>
kube-system               kube-proxy-x4xtp                                            19m         100m            <none>          15Mi           <none>              <none>
kube-system               kube-proxy-xlpn7                                            0m          100m            <none>          0Mi            <none>              <none>
metrics-server            metrics-server-5875c7d795-bj7cq                             5m          200m            500m            29Mi           200Mi               500Mi
metrics-server            metrics-server-5875c7d795-jpjjn                             7m          200m            500m            29Mi           200Mi               500Mi
gitlab-runner-s           runner-heq8ujaj-project-10386-concurrent-06t94f             <wait>      200m,100m       200m,200m       <wait>         200Mi,128Mi         500Mi,500Mi
gitlab-runner-s           runner-heq8ujaj-project-10386-concurrent-10lpn9j            1m          200m,100m       200m,200m       12Mi           200Mi,128Mi         500Mi,500Mi
gitlab-runner-s           runner-heq8ujaj-project-10386-concurrent-11jrxfh            <wait>      200m,100m       200m,200m       <wait>         200Mi,128Mi         500Mi,500Mi
gitlab-runner-s           runner-heq8ujaj-project-10386-concurrent-129hpvl            1m          200m,100m       200m,200m       12Mi           200Mi,128Mi         500Mi,500Mi
gitlab-runner-s           runner-heq8ujaj-project-10386-concurrent-13kswg8            1m          200m,100m       200m,200m       12Mi           200Mi,128Mi         500Mi,500Mi
gitlab-runner-s           runner-heq8ujaj-project-10386-concurrent-15qhp5w            <wait>      200m,100m       200m,200m       <wait>         200Mi,128Mi         500Mi,500Mi

Noteworthy: You can sort over CPU consumption with e.g.:

| awk 'NR<2{print $0;next}{print $0| "sort --key 3 --numeric -b --reverse"}

This works on Mac - I am not sure, if it works on Linux, too (because of join, sort, etc...).

Hopefully, someone can use this till kubectl gets a good view for that.

I have a good experience with kube-capacity.

Example:

kube-capacity --util

NODE              CPU REQUESTS    CPU LIMITS    CPU UTIL    MEMORY REQUESTS    MEMORY LIMITS   MEMORY UTIL
*                 560m (28%)      130m (7%)     40m (2%)    572Mi (9%)         770Mi (13%)     470Mi (8%)
example-node-1    220m (22%)      10m (1%)      10m (1%)    192Mi (6%)         360Mi (12%)     210Mi (7%)
example-node-2    340m (34%)      120m (12%)    30m (3%)    380Mi (13%)        410Mi (14%)     260Mi (9%)

In order for this tool to be truly useful it should detect all kubernetes device plugins deployed on cluster and show usage for all of them. CPU/Mem is definetly not enough. There's also GPUs, TPUs (for machine learning), Intel QAT and probably more I don't know about. Also what about storage? I should be able to easily see what was requested and what is used (ideally in terms of iops as well).

@boniek83 , It's why I created kubectl-view-allocations, because I need to list GPU,... any feedback (on the github project) are welcomes. I curious to know if it detects TPU (it should if it is listed as a Node's resources)

@boniek83 , It's why I created kubectl-view-allocations, because I need to list GPU,... any feedback (on the github project) are welcomes. I curious to know if it detects TPU (it should if it is listed as a Node's resources)

I'm aware of your tool and, for my purpose, it is the best that is currently available. Thanks for making it!
I will try to get TPUs tested after Easter. It would be helpful if this data would be available in web app format with pretty graphs so I wouldn't have to give any access to kubernetes to data scientists. They only want to know who is eating away resources and nothing more :)

Since none of the tools and scripts above fit my needs (and this issue is still open :( ), I hacked my own variant:
https://github.com/eht16/kube-cargo-load

It provides a quick overview of PODs in a cluster and shows their configured memory requests and limits and the actual memory usage. The idea is to get a picture of the ratio between configured memory limits and actual usage.

How can we get memory dumps logs of the pods?
Pods are often getting hung,

• kubectl describe nodes OR kubectl top nodes , which one should be considered to calculate cluster resource utilization ?
• Also Why there is difference between these 2 results.
  Is there any logical explanation this yet ?

/kind feature

All the comments and hacks with nodes worked well for me. I also need something for a higher view to keep track of..like sum of resources per node pool !

hi,
I want to log the cpu and memory usage for a pod , every 5 mins over a period of time. I would then use this data to create a graph in excel. Any ideas? Thanks

Hi,
I'm happy to see that Google pointed all of us to this issue :-) (a bit disappointed that it's still open after almost 5y.) Thanks for all the shell snips and other tools.

Simple and quick hack:

$ kubectl describe nodes | grep 'Name:\|  cpu\|  memory'

Name:               XXX-2-wke2
  cpu                                               1552m (77%)   2402m (120%)
  memory                                            2185Mi (70%)  3854Mi (123%)
Name:               XXX-2-wkep
  cpu                                               1102m (55%)   1452m (72%)
  memory                                            1601Mi (51%)  2148Mi (69%)
Name:               XXX-2-wkwz
  cpu                                               852m (42%)    1352m (67%)
  memory                                            1125Mi (36%)  3624Mi (116%)

Simple and quick hack:

$ kubectl describe nodes | grep 'Name:\|  cpu\|  memory'

Name:               XXX-2-wke2
  cpu                                               1552m (77%)   2402m (120%)
  memory                                            2185Mi (70%)  3854Mi (123%)
Name:               XXX-2-wkep
  cpu                                               1102m (55%)   1452m (72%)
  memory                                            1601Mi (51%)  2148Mi (69%)
Name:               XXX-2-wkwz
  cpu                                               852m (42%)    1352m (67%)
  memory                                            1125Mi (36%)  3624Mi (116%)

Device plugins are not there. They should be. Such devices are resources as well.

Hello!

I created this script and share it with you.

https://github.com/Sensedia/open-tools/blob/master/scripts/listK8sHardwareResources.sh

This script has a compilation of some of the ideas you shared here. The script can be incremented and can help other people get the metrics more simply.

Thanks for sharing the tips and commands!

For my use case, I ended up writing a simple kubectl plugin that lists CPU/RAM limits/reservations for nodes in a table. It also checks current pod CPU/RAM consumption (like kubectl top pods), but ordering output by CPU in descending order.

Its more of a convenience thing than anything else, but maybe someone else will find it useful too.

https://github.com/laurybueno/kubectl-hoggers

Whoa, what a huge thread and still no proper solution from kubernetes team to properly calculate current overall cpu usage of a whole cluster?

For those looking to run this on minikube , first enable the metric server add-on
minikube addons enable metrics-server
and then run the command
kubectl top nodes

If you're using Krew:

kubectl krew install resource-capacity
kubectl resource-capacity

NODE                                          CPU REQUESTS   CPU LIMITS     MEMORY REQUESTS   MEMORY LIMITS
*                                             16960m (35%)   18600m (39%)   26366Mi (14%)     3100Mi (1%)
ip-10-0-138-176.eu-north-1.compute.internal   2460m (31%)    4200m (53%)    567Mi (1%)        784Mi (2%)
ip-10-0-155-49.eu-north-1.compute.internal    2160m (27%)    2200m (27%)    4303Mi (14%)      414Mi (1%)
ip-10-0-162-84.eu-north-1.compute.internal    3860m (48%)    3900m (49%)    8399Mi (27%)      414Mi (1%)
ip-10-0-200-101.eu-north-1.compute.internal   2160m (27%)    2200m (27%)    4303Mi (14%)      414Mi (1%)
ip-10-0-231-146.eu-north-1.compute.internal   2160m (27%)    2200m (27%)    4303Mi (14%)      414Mi (1%)
ip-10-0-251-167.eu-north-1.compute.internal   4160m (52%)    3900m (49%)    4491Mi (14%)      660Mi (2%)