Memory Footprint Test

Why measure memory footprint?

  • This platform is designed for a light-weight edge computing deployment, capable of running on devices with few resources (for example, 256MB RAM)
  • It is important to know when deploying many pods that it showcases as little memory footprint as possible

KPI’s measured

  • %CPU
  • %Memory
  • Resident Set Size (RSS)

How to test

After deployment and provisioning of KubeEdge cloud and edge components in 2 VM’s (supported and tested over Ubuntu 16.04) respectively, start deploying pods from 0 to 100 in steps of 5. Keep capturing above KPI’s using standard linux ps commands, after each step.

Test setup

KubeEdge Test Setup

Fig 1: KubeEdge Test Setup

Creating a setup


  • Host machine’s or VM’s resource requirements can mirror the edge device of your choice
  • Resources used for above setup are 4 CPU, 8GB RAM and 200 GB Disk space. OS is Ubuntu 16.04.
  • Docker image used to deploy the pods in edge, needs to be created. The steps are:
    1. Go to
    2. Using the Dockerfile available here and create docker image (perftestimg:v1).
    3. Execute the docker command sudo docker build --tag "perftestimg:v1" ., to get the image.


  • For KubeEdge Cloud and Edge:

    Please follow steps mentioned in KubeEdge

  • For docker image:

  • Deploy docker registry to either edge on any VM or host which is reachable to edge. Follow the steps mentioned here:

  • Create perftestimg:v1 docker image on the above mentioned host

  • Then push this image to docker registry using docker tag and docker push commands (Refer: Same docker registry url mentioned above) [Use this image’s metadata in pod deployment yaml]


  1. Check edge node is connected to cloud. In cloud console/terminal, execute the below command

    root@ubuntu:~/edge/pod_yamls# kubectl get nodes
    NAME                                   STATUS     ROLES    AGE     VERSION                          Unknown    <none>   11s
    ubuntu                                 NotReady   master   5m22s   v1.14.0
  2. On cloud, modify deployment yaml (, set the image name and set spec.replica as 5

  3. Execute sudo kubectl create -f ./perftestimg.yaml to deploy the first of 5 pods in edge node

  4. Execute sudo kubectl get pods | grep Running | wc to check if all the pods come to Running state. Once all pods come to running state, go to edge VM

  5. On Edge console, execute ps -aux | grep edgecore. The output shall be something like:

    root     102452  1.0  0.5 871704 42784 pts/0    Sl+  17:56   0:00 ./edgecore
    root     102779  0.0  0.0  14224   936 pts/2    S+   17:56   0:00 grep --color=auto edge
  6. Collect %CPU, %MEM and RSS from respective columns and record

  7. Repeat step 2 and this time increase the replica by 5

  8. This time execute sudo kubectl apply -f <PATH>/perftestimg.yaml

  9. Repeat steps from 4 to 6.

  10. Now repeat steps from 7 to 9, till the replica count reaches 100