Specifying memory in Kubernetes pods for deployment of Docker image

0
votes

I am exploring about implementation of Kubernetes cluster and deployment into Kubernetes cluster using Jenkins via CI/CD pipeline. When exploring I found that we don't need to define the worker machine node where we need to deploy our pods. Kubernetes master will take care for where to deploy / free pod in worker machine for deployment. We only need to define how much memory need to that pod in definition.

Here my confusion is that, Already we assigned and configured Kubernetes cluster for deployment. That all nodes containing its own memory according to creation of AWS EC2 (since I am planning to use AWS Ec2 - Ubuntu 16.04 LTS).

So why we again need to define memory in pod ? Is that proper way of pod deployment ?

I am only started in CI/CD pipeline world.

1
kubernetesmemory

1 Answers

4
votes

Specifying memory and cpu in the pod specification is completely optional. Still there are a couple of aspects to specifying memory and CPU at pod level:

  • As explained here, if you don't specify CPU/memory - the pod/container can consume all resources on that node and potentially affect other pod/containers running on that node.

  • Each application should specify the memory and CPU they need for running the application. This information is used by Kubernetes during scheduling the pod on one of the nodes in the cluster where enough resources are available. This information ensures better scheduling decisions.

  • It enables the Horizontal Pod Autoscaler (HPA) to scale the pods when the resource consumption beyond a certain limit. The details are explained in this doc. Unless there is a memory/cpu limit specified, you can not calculate that the pod is running 80% of that metric and it should be scaled into two replicas.

  • You can also enable a certain default at namespace level and then only override for specific applications, details here