I've got some deployment on a basic k8s cluster withouth defining requests and limits.
Is there any way to check how much the pod is asking for memory and cpu?
Depending on whether the metrics-server is installed in your cluster, you can use:
kubectl top pod
kubectl top node
After installing the Metrics Server, you can query the Resource Metrics API directly for the resource usages of pods and nodes:
All nodes in the cluster:
kubectl get --raw=/apis/metrics.k8s.io/v1beta1/nodes
A specific node:
kubectl get --raw=/apis/metrics.k8s.io/v1beta1/nodes/{node}
All pods in the cluster:
kubectl get --raw=/apis/metrics.k8s.io/v1beta1/pods
All pods in a specific namespace:
kubectl get --raw=/apis/metrics.k8s.io/v1beta1/namespaces/{namespace}/pods
A specific pod:
kubectl get --raw=/apis/metrics.k8s.io/v1beta1/namespaces/{namespace}/pods/{pod}
The API returns you the absolute CPU and memory usages of the pods and nodes.
From this, you should be able to figure out how much resources each pod consumes and how much free resources are left on each node.
Related
Is there a way query cpu request and limit with kubectl for each container in a kubernetes context / namespace, just as I can query cpu usage with kubectl top pods.
Requests and limits are the mechanisms Kubernetes uses to control resources such as CPU and memory. Requests are what the container is guaranteed to get. If a container requests a resource, Kubernetes will only schedule it on a node that can give it that resource. Limits, on the other hand, make sure a container never goes above a certain value. The container is only allowed to go up to the limit, and then it is restricted.Limit can never be lower than the request.
As said by #chris, try the following commands for cpu requests and limits for kubernetes namespaces
You can get the pods and their CPU requests with the following command.
kubectl get pods --all-namespaces -o=jsonpath="{range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}{range .spec.containers[*]} {.name}:{.resources.requests.cpu}{'\n'}{end}{'\n'}{end}"
You can get the pods and their CPU Limits with the following command.
kubectl get pods --all-namespaces -o=jsonpath="{range .items[*]}{.metadata.namespace}:{.metadata.name}{'\n'}{range .spec.containers[*]} {.name}:{.resources.limits.cpu}{'\n'}{end}{'\n'}{end}"
K8s VERSION = v1.18.6
I have deployed the Kubernetes dashboard using the following command and added a privileged user with which I logged into the dashboard.
but not able to see Pods CPU and Memory Utilization graphs are missing Kubernetes dashboard
The Kubernetes Metrics Server is an aggregator of resource usage data in your cluster,
To deploy the Metrics Server
Deploy the Metrics Server with the following command:
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/download/v0.3.6/components.yaml
Verify that the metrics-server deployment is running the desired number of pods with the following command.
kubectl get deployment metrics-server -n kube-system
Output
NAME READY UP-TO-DATE AVAILABLE AGE
metrics-server 1/1 1 1 6m
Also you can validate by below command:
kubectl top nodes
to see node cpu utilisation if it works, it should then come up in Dashboard as well.
Resource usage metrics are only available for K8s clusters once Metrics Server has been installed.
Cluster information:
Kubernetes version: 1.12.8-gke.10
Cloud being used: GKE
Installation method: gcloud
Host OS: (machine type) n1-standard-1
CNI and version: default
CRI and version: default
During node scaling, HPA couldn't get CPU metric.
At the same time, kubectl top pod and kubectl top node output is:
Error from server (ServiceUnavailable): the server is currently unable to handle the request (get pods.metrics.k8s.io)
Error from server (ServiceUnavailable): the server is currently unable to handle the request (get nodes.metrics.k8s.io)
For more details, I'll show you the flow of my problem occurs:
Suddenly many requests arrive at the GKE server. (Using testing tool)
HPA detects current CPU usage above target CPU usage(50%), thus try pod scale up
incrementally.
Insufficient CPU warning occurs when creating pods, thus GKE try node scalie up
incrementally.
Soon the HPA fails to get the metric, and kubectl top node or kubectl top pod
doesn’t get a response.
- At this time one or more OutOfcpu pods are found, and several pods are in
ContainerCreating (from Pending state).
After node scale-up is complete and some time has elapsed (about a few minutes),
HPA starts to fetch the CPU metric successfully and try to scale up/down based on
metric.
Same situation happens when node scale down.
This causes pod scaling to stop and raises some failures on responding to client’s requests. Is this normal?
I think HPA should get CPU metric(or other metrics) on running pods even during node scaling, to keep track of the optimal pod size at the moment. So when node scaling done, HPA create the necessary pods at once (rather than incrementally).
Can I make my cluster work like this?
Maybe your node runs out of one resource either memory or cpu, there are config maps that describe how addons are scaled depending on the cluster size. You need to edit metrics-server-config config map in kube-system namespace:
kubectl edit cm/metrics-server-config -n kube-system
you should add
baseCPU
cpuPerNode
baseMemory
memoryPerNode
to NannyConfiguration, here you can find extensive manual:
Also heapster suffers from the same OOM issue: too many pods to handle all metrics within assigned resources please modify heapster's config map in accordingly:
kubectl edit cm/heapster-config -n kube-system
k8s version: 1.12.1
I created pod with api on node and allocated an IP (through flanneld). When I used the kubectl describe pod command, I could not get the pod IP, and there was no such IP in etcd storage.
It was only a few minutes later that the IP could be obtained, and then kubectl get pod STATUS was Running.
Has anyone ever encountered this problem?
Like MatthiasSommer mentioned in comment, process of creating pod might take a while.
If POD will stay for a longer time in ContainerCreating status you can check what is stopping it change to status Running by command:
kubectl describe pod <pod_name>
Why creating of pod may take a longer time?
Depends on what is included in manifest, pod can share namespace, storage volumes, secrets, assignin resources, configmaps etc.
kube-apiserver validates and configures data for api objects.
kube-scheduler needs to check and collect resurces requrements, constraints, etc and assign pod to the node.
kubelet is running on each node and is ensures that all containers fulfill pod specification and are healty.
kube-proxy is also running on each node and it is responsible for network on pod.
As you see there are many requests, validates, syncs and it need a while to create pod fulfill all requirements.
I'm using digital ocean kubernetes cluster service and have deployed 9 nodes in cluster but when i'm trying to deploy kafka zookeeper pods few pods get deployed other remain in pending state. i've tried doing
kubectl describe pods podname -n namespace
it shows
its not getting assigned to any nodes
check if your deployment/statefulset might have some node Selectors and/or node/pod affinity that might prevent it from running .
also it would be helpful to see more parts of the pod decribe since it might give more details.
there is a message on your print screen about the PersistentVolume Claims so I would also check the status of the pvc objects to check if they are bound or not.
good luck