I have a EKS cluster running with cluster-autoscaler version 1.21.2 deployed. When I did a kubectl top nodes, I found a node using 5% cpu and 21% memory utilised. But in cluster-autoscaler pod log, I see below message for the same node:
Node XXXX is not suitable for removal - cpu utilization too big (0.663130)
I'm now confused how is cluster autoscaler calculating this value and why is the node not scaled down. BTW, I used default config of --scale-down-utilization-threshold=0.5
We stumbled upon the same issue, and realized that the CPU utilization value (in your case 66,31%) matches roughly the amount of CPU requested by the pods/containers running on the node.
Remember: Requested CPU (and other resources) by a pod/container is given guaranteed.
This is why it sounds logical to us that when looking at the node's actual CPU usage, it might be idle, though from a Kubernetes autoscaling perspective, the node uses 66% from the CPU.
Related
Having a HPA configuration of 50% average CPU
kubectl autoscale deployment php-apache --cpu-percent=50 --min=1 --max=10
I found the problem that I have only one pod receiving traffic so the CPU is higher than 50% of request cpu.
Then start auto scaling up new pods, but those sometimes are not receiving yet any traffic, so the cpu consumption is very low.
My expectations was to see those pods that dont use any cpu to be scale down at some point(how much it should take?), but it's not happening, and I believe the reason is, that first condition of one pod cpu use, higher than 50% is forcing to keep those pods up.
What I need is to scale up/down those pods, until they can start receiving traffic, which it depends on in which node they are deployed.
Any suggestion of how to accomplish this issue?
i set hpa for my deployment/app, for example, CPU 80%.
my app deployment has two containers, one is app for traffic, the other is automatically injected istio-proxy.
when i get hpa during running traffic, i found something unexpected for the hpa result.
the cpu request of istio-proxy is 2G.
the cpu request of app is 4G.
the cpu consumed of istio-proxy is 1G.
the cpu consumed of app is 4G.
so, i expected the hpa of this pod (including 2 containers) is (1+2)/(2+4) = 50%.
but the actual result is close to (1+2)/4 = 75%.
it seems the istio-proxy's cpu request is excluded from calculating cpu utilization of hpa.
as i know, k8s get cpu requests from deployment, but actually for this sidecar auto injection case, the deployment yaml doesn't have any istio-proxy container information.
i guess that's why the istio-proxy cpu request is excluded.
but is that the expected behavior or a bug ?
I think as of 1.19, the hpa works on an average value of all containers in the pods. The exact logic is here : https://github.com/kubernetes/kubernetes/blob/v1.9.0/pkg/controller/podautoscaler/metrics/utilization.go#L49
currentUtilization = int32((metricsTotal * 100) / requestsTotal)
As per the above logic HPA is calculating pod cpu utilization as total cpu usage of all containers in pod divided by total request
I have a node pool for one deployment with 200-1000 pods. They're set with a CPU based HPA.
When the HPA scales down the deployment, it removes pods randomly, and eventually, I have an under-utilized node pool. The nodes aren't scaled down correctly because they still have at least one pod running.
I tried to find a solution and failed. Possible solutions, in my opinion:
HPA is aware of nodes utilization.
A PodDisruptionBudget for nodes?
Drain node if its CPU utilization is under a threshold.
Any help will be much appreciated.
I have a Kubernetes cluster and when I try to scale a Deployment up to 8 pods, it gives an error message:
"0/3 nodes are available: 3 insufficient cpu."
After some time it shows 3/8 pods available and then 5/8 pods available with the same error, but never reached 8 pods.
Recently we introduced CPU limits on Pods.
What is the cause and solution for this error?
Scheduler is not able to schedule pods to any of 3 nodes as required resources are not available on nodes.
This may be due to cpu request value of pod is more than available cpu of nodes or actually your nodes don't have any cpu capacity left to schedule new pods.
Check available cpu capacity of nodes and increase it by removing non required pods. Also reduce cpu request value of pod if specified.
I'm defining this autoscaler with kubernetes and GCE and I'm wondering what exactly should I specify for targetCPUUtilizationPercentage. That target points to what exactly? Is it the total CPU in my cluster? When the pods referenced in this autoscaler consume more than targetCPUUtilizationPercentage what happens?
The CPU utilization is the average CPU usage of a all pods in a deployment across the last minute divided by the requested CPU of this deployment. If the mean of the pods' CPU utilization is higher than the target you defined, the your replicas will be adjusted.
You can read more about this topic here.
This is average cpu utilisation of all the pods, so if you have given CPU as 200 in the resource requests and targetCPUUtilizationPercentage as 80%, then at 160 value of threshold, it will scale out the pod. It will create a new repliace.