Running an experiment on EdgeNet

If you are familiar with Docker and Kubernetes, you already know almost everything that you need to know to deploy experiments on EdgeNet. If not, you can rely on the wealth of documentation and tutorials already available for these technologies online. This page describes the basic steps required to run an experiment on EdgeNet, with attention to the few EdgeNet-specific features: user registration, user namespaces and selective deployments.

CPU architecture

EdgeNet supports both nodes with ARM64 and x86-64 CPUs. If the binaries in your image do not match the target node architecture, it will fail to run with the message: exec user process caused "exec format error". For example, if you build a C++ program in your Dockerfile, this program will by default be compiled for the architecture of your machine: If you’re running Docker on an Intel MacBook, it will produce an x86-64 binary, while if you run it on an M1 MacBook, it will produce an ARM64 binary.

Docker also supports building multi-architecture image on a single machine, by emulating the target CPUs architecture. The following tutorials provides more information:

• Building Multi-Arch Images for Arm and x86 with Docker Desktop
• Continuous Cross-Architecture Integration with GitLab

Deploying containers

Creating a pod

Here is an example deployment.yaml file:

# deployment.yaml
apiVersion: apps.edgenet.io/v1alpha
kind: SelectiveDeployment
metadata:
  name: simple-experiment
  namespace: your-tenant
spec:
  workloads:
    daemonset:
      - apiVersion: apps/v1
        kind: DaemonSet
        metadata:
          name: simple-experiment
          namespace: your-tenant
          labels:
            app: simple-experiment
        spec:
          selector:
            matchLabels:
              app: simple-experiment
          template:
            metadata:
              labels:
                app: simple-experiment
            spec:
              containers:
                - name: simple-experiment
                  image: username/simple-experiment:1.0
                  ports:
                    - containerPort: 80
                  resources:
                    limits:
                      cpu: 100m
                      memory: 125Mi
                    requests:
                      cpu: 100m
                      memory: 125Mi
  selector:
    - value:
        - North_America
        - Europe
      operator: In
      quantity: 5
      name: Continent

And here is the command to launch it (provide the correct path to your kubeconfig file):

kubectl --kubeconfig /path/to/kubeconfig.cfg apply -f deployment.yaml

Monitoring the experiment

These commands allow you to find the pod names and to forward the container port. We omit the --kubeconfig and -n options for brevity here.

View the selective deployment (sd) status:

kubectl --kubeconfig /path/to/kubeconfig.cfg -n your-tenant \
    describe sd simple-experiment 

View the daemon set (ds) status:

kubectl --kubeconfig /path/to/kubeconfig.cfg -n your-tenant \
  describe ds simple-experiment

View the logs of a pod:

kubectl --kubeconfig /path/to/kubeconfig.cfg -n your-tenant \
    logs POD_NAME

Forward the ports of a pod:

kubectl --kubeconfig /path/to/kubeconfig.cfg -n your-tenant \
    port-forward POD_NAME 8080:80

Stopping the experiment

kubectl --kubeconfig /path/to/kubeconfig.cfg delete -f deployment.yaml

Tips

To avoid passing --kubeconfig on each command, you can copy your kubeconfig file to $HOME/.kube/config, or export the KUBECONFIG variable. For example, export KUBECONFIG=/home/user/Downloads/kubeconfig.cfg.

To avoid passing -n/--namespace on each command, you can use a tool like kubectx.

Going further

For more information, please refer to the Docker and Kubernetes documentation.