Setting Ressource limit for ElasticSearch in Kubernetes creates bug - elasticsearch

Question

I have a web App, that I am trying to deploy with Kubernetes. It's working correctly, but when I try to add resource limits, the ElasticSearch will not deploy.
elasticsearch-deployment.yaml:
apiVersion: v1
kind: Service
metadata:
name: elasticsearch-service
spec:
type: NodePort
selector:
app: elasticsearch
ports:
- port: 9200
targetPort: 9200
name: serving
- port: 9300
targetPort: 9300
name: node-to-node
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: elasticsearch-deployment
labels:
app: elasticsearch
spec:
replicas: 1
selector:
matchLabels:
app: elasticsearch
template:
metadata:
labels:
app: elasticsearch
spec:
containers:
- name: elasticsearch
image: elasticsearch:7.9.0
ports:
- containerPort: 9200
- containerPort: 9300
env:
- name: discovery.type
value: single-node
# resources:
# limits:
# memory: 8Gi
# cpu: "4"
# requests:
# memory: 4Gi
# cpu: "2"
If I uncomment the resources section of the file, the pod is stuck in pending:
> kubectl get pods
NAME READY STATUS RESTARTS AGE
backend-deployment-bd4f98697-rxsz8 1/1 Running 1 (6m9s ago) 6m40s
elasticsearch-deployment-644475545b-t75pp 0/1 Pending 0 6m40s
frontend-deployment-8bc989f89-4g6v7 1/1 Running 0 6m40s
mysql-0 1/1 Running 0 6m40s
If I check the events:
> kubectl get events
...
Warning FailedScheduling pod/elasticsearch-deployment-54d9cdd879-k69js 0/1 nodes are available: 1 Insufficient cpu.
Warning FailedScheduling pod/elasticsearch-deployment-54d9cdd879-rjj24 0/1 nodes are available: 1 Insufficient cpu.
...
The events says that the pod has Insufficient cpu, but I tried to change the resource limits to :
resources:
limits:
memory: 8Gi
cpu: "18"
requests:
memory: 4Gi
cpu: "18"
Still doesn't works, the only way for it to works is to remove the resource limit, but why?

Answer 1

It is because of the request, not the limit. It means your node doesn't have enough memory to schedule a pod that requests 2 CPUs. You need to set the value to a lower one (e.g. 500m).
You can check your server's allocatable CPUs. The sum of all Pod's CPU requests should be lower than this.
# kubectl describe nodes
...
Allocatable:
cpu: 28
...

Answer 2

In Addition to Daigo
Requests and limits are on a per-container basis. Each container in the Pod gets its own individual limit and request. When adding the limits and requests for each container together, you will get an aggregate value for the Pod.
Combining the requests and limits value of each container will represent the Pod requests which is 500m cpu and 128Mi memory and Pod limits is 1 cpu and 256Mi memory.
Requests are what the container is guaranteed to get. If a container requests a resource, k8s will only schedule it on a node that can give it that resource.
Limits, on the other hand, make sure a container won't go above a certain value or limit.
Without requests and limits defined, the scheduler might place the Pod on a node that has less than 1 GiB memory available.