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Step-by-step instructions for performing operations with Kubernetes.

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Assign CPU and RAM Resources to a Container

This page shows how to assign CPU and RAM resources to containers running in a Kubernetes Pod.

Before you begin

You need to have a Kubernetes cluster, and the kubectl command-line tool must be configured to communicate with your cluster. If you do not already have a cluster, you can create one by using Minikube, or you can use one of these Kubernetes playgrounds:

Assign CPU and RAM resources to a container

When you create a Pod, you can request CPU and RAM resources for the containers that run in the Pod. You can also set limits for CPU and RAM resources. To request CPU and RAM resources, include the resources:requests field in the configuration file. To set limits on CPU and RAM resources, include the resources:limits field.

Kubernetes schedules a Pod to run on a Node only if the Node has enough CPU and RAM available to satisfy the total CPU and RAM requested by all of the containers in the Pod. Also, as a container runs on a Node, Kubernetes doesn’t allow the CPU and RAM consumed by the container to exceed the limits you specify for the container. If a container exceeds its RAM limit, it is terminated. If a container exceeds its CPU limit, it becomes a candidate for having its CPU use throttled.

In this exercise, you create a Pod that runs one container. The configuration file for the Pod requests 250 milicpu and 64 mebibytes of RAM. It also sets upper limits of 1 cpu and 128 mebibytes of RAM. Here is the configuration file for the Pod:

cpu-ram.yaml 
apiVersion: v1
kind: Pod
metadata:
  name: cpu-ram-demo
spec:
  containers:
  - name: cpu-ram-demo-container
    image: gcr.io/google-samples/node-hello:1.0
    resources:
      requests:
        memory: "64Mi"
        cpu: "250m"
      limits:
        memory: "128Mi"
        cpu: "1"

  1. Create a Pod based on the YAML configuration file:

     kubectl create -f https://k8s.io/docs/tasks/configure-pod-container/cpu-ram.yaml

  2. Display information about the pod:

     kubectl describe pod cpu-ram-demo

    The output is similar to this:

     Name:   cpu-ram-demo
 ...
 Containers:
   cpu-ram-demo-container:
    ...
     Limits:
       cpu:  1
       memory: 128Mi
     Requests:
       cpu:    250m
       memory:   64Mi

CPU and RAM units

The CPU resource is measured in cpus. Fractional values are allowed. You can use the suffix m to mean mili. For example 100m cpu is 100 milicpu, and is the same as 0.1 cpu.

The RAM resource is measured in bytes. You can express RAM as a plain integer or a fixed-point integer with one of these suffixes: E, P, T, G, M, K, Ei, Pi, Ti, Gi, Mi, Ki. For example, the following represent approximately the same value:

128974848, 129e6, 129M , 123Mi

If you’re not sure how much resources to request, you can first launch the application without specifying resources, and use resource usage monitoring to determine appropriate values.

If a Container exceeds its RAM limit, it dies from an out-of-memory condition. You can improve reliability by specifying a value that is a little higher than what you expect to use.

If you specify a request, a Pod is guaranteed to be able to use that much of the resource. See Resource QoS for the difference between resource limits and requests.

If you don’t specify limits or requests

If you don’t specify a RAM limit, Kubernetes places no upper bound on the amount of RAM a Container can use. A Container could use all the RAM available on the Node where the Container is running. Similarly, if you don’t specify a CPU limit, Kubernetes places no upper bound on CPU resources, and a Container could use all of the CPU resources available on the Node.

Default limits are applied according to a limit range for the default namespace. You can use kubectl describe limitrange limits to see the default limits.

For information about why you would want to specify limits, see Setting Pod CPU and Memory Limits.

For information about what happens if you don’t specify CPU and RAM requests, see Resource Requests and Limits of Pod and Container.

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