DEV Community

Yash Gangwar
Yash Gangwar

Posted on

How you can run your first Argo Workflow on K3s ?

Welcome!

Argo Workflows is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. Argo Workflows is implemented as a Kubernetes CRD (Custom Resource Definition). In simple words, Argo is a workflow scheduler where you can run your workflows onto a Kubernetes Cluster, you can containerize different steps within your workflow and then all those steps could be executed as a part of your workflow onto a Kubernets cluster using Argo workflows. Read more

Here we gonna create a simple Argo workflow template that will echo "hello world" using the docker/whalesay container image and this container will be running on our K3s cluster using Argo Workflow template.

Let's get started!! 🚀

Before starting

Before proceeding further with the hands-on we need to have some tools and CLI installed locally:

  1. Docker: A containerization tool that we will be using for running K3s cluster on container. Download it from here. To check your installation run command docker --version.

Output:

   Docker version 20.10.11, build dea9396
Enter fullscreen mode Exit fullscreen mode
  1. kubectl: Kubernetes command-line tool that allows you to run commands against Kubernetes clusters. Download it from here. To check your installation run command kubectl version --client.

Output:

   Client Version: version.Info{Major:"1", Minor:"22", GitVersion:"v1.22.0", GitCommit:"c2b5237ccd9c0f1d600d3072634ca66cefdf272f", GitTreeState:"clean", BuildDate:"2021-08-04T18:03:20Z", GoVersion:"go1.16.6", Compiler:"gc", Platform:"windows/amd64"}
Enter fullscreen mode Exit fullscreen mode
  1. argo: Argo CLI allows to (amongst other things) submit, watch, and list workflows. Download it from here. To check your installation run command argo version.

Output:

   argo: v3.2.4
    BuildDate: 2021-11-18T00:28:05Z
    GitCommit: 8771ca279c329753e420dbdd986a9c914876b151
    GitTreeState: clean
    GitTag: v3.2.4
    GoVersion: go1.16.10
    Compiler: gc
    Platform: windows/amd64
Enter fullscreen mode Exit fullscreen mode

Setting up K3s cluster locally(on Docker)

K3s is a fully conformant lightweight production-ready Kubernetes distribution. As compared to K8s, its easy to install, packaged as a single binary, requires less resources which means it's possible to run a kubernets cluster on anything from 512MB of RAM machines upwards, and we can install it in a fraction of the time, unlike regular K8s.

We are going to use K3d, which is a utility designed to easily run k3s in Docker.K3d makes it very easy to create single and multi-node k3s clusters in docker for local development on Kubernetes.

✅ Step 1: Install scripts of current latest release

curl -s https://raw.githubusercontent.com/rancher/k3d/main/install.sh | bash
Enter fullscreen mode Exit fullscreen mode

If this command doesn't works, you can grab a release binary from the Github release tab and install it yourself.

✅ Step 2: Create a cluster named myK3sCluster with just a single server node

k3d cluster create myK3sCluster
Enter fullscreen mode Exit fullscreen mode

This command will download the docker image of K3s and setup our cluster on container.

✅ Step 3: To check if myK3sCluster is successfully running on docker

kubectl get nodes
Enter fullscreen mode Exit fullscreen mode

Output:

NAME                        STATUS   ROLES                  AGE     VERSION
k3d-myk3scluster-server-0   Ready    control-plane,master   7h57m   v1.21.7+k3s1
Enter fullscreen mode Exit fullscreen mode

Installing Argo Workflows in our K3s cluster

✅ Step 1: Creating a separate namespace for argo inside our cluster

kubectl create ns argo
kubectl get ns
Enter fullscreen mode Exit fullscreen mode

Output:

NAME              STATUS   AGE
default           Active   8h
kube-system       Active   8h
kube-public       Active   8h
kube-node-lease   Active   8h
argo              Active   8h
Enter fullscreen mode Exit fullscreen mode

✅ Step 2: Install Argo Workflows

To get started quickly, we can use the quick start manifest which will install Argo Workflow as well as some commonly used components

kubectl apply -n argo -f https://raw.githubusercontent.com/argoproj/argo-workflows/master/manifests/quick-start-postgres.yaml
Enter fullscreen mode Exit fullscreen mode

✅ Step 3: Check installation

Verify everything is up running. We need to wait till each pod has running or completed status before moving on.

kubectl get pods -n argo
Enter fullscreen mode Exit fullscreen mode

Output:

NAME                                  READY   STATUS      RESTARTS   AGE
minio-79566d86cb-82c4j                1/1     Running     1          8h
postgres-546d9d68b-8dfqp              1/1     Running     1          8h
workflow-controller-558db44f7-wglh5   1/1     Running     5          8h
argo-server-5d58f6585d-7jx2p          1/1     Running     4          8h
Enter fullscreen mode Exit fullscreen mode

✅ Step 4: Accessing Argo Workflows dashboard

As we are running Argo Workflows locally, we can open a port-forward so you can access the namespace/dashboard.

kubectl -n argo port-forward deployment/argo-server 2746:2746
Enter fullscreen mode Exit fullscreen mode

Open the Argo dashboard using URL https://localhost:2746. Here you can see all your workflows, create them and manage them.

Creating our first Argo Workflow template

I have created a very simple workflow template to echo "hello world" using the docker/whalesay container image from DockerHub. Create a file named hello-world.yaml, and copy paste the following code.

apiVersion: argoproj.io/v1alpha1
kind: Workflow # new type of k8s spec used to create argo workflows
metadata:
  generateName: hello-world- # name of the workflow spec
spec:
  entrypoint: whalesay # specifies the initial template that should be invoked i.e whalesay
  templates:
    - name: whalesay # name of the template
      container: # container that will run when this template in invoked
        image: docker/whalesay # image that will run inside the cluster
        command: [cowsay]
        args: ["hello world"]
        resources: # limit the resources
          limits:
            memory: 32Mi
            cpu: 100m
Enter fullscreen mode Exit fullscreen mode

✅ Step 1: Submitting our workflow

Make sure before running the following codes you should be the folder where you created your hello-world.yaml file.

argo submit -n argo --watch hello-world.yaml
Enter fullscreen mode Exit fullscreen mode

Output:

Name:                hello-world-xpc6d
Namespace:           argo
ServiceAccount:      default
Status:              Running
reated:              Tue Jan 18 22:32:07 +0530 (6 seconds ago)
Started:             Tue Jan 18 22:32:07 +0530 (6 seconds ago)
Duration:            6 seconds
Progress:            0/0

STEP                  TEMPLATE  PODNAME            DURATION  MESSAGE
 â—· hello-world-xpc6d  whalesay  hello-world-xpc6d  6s
Enter fullscreen mode Exit fullscreen mode

You can see your workflow named hello-world-xpc6d has started running. Wait till it has finished executing. You can also see your workflow on the dashboard

✅ Step 2: Getting logs of our workflow

Here, @latest tag refers to the recent or the last submitted workflow. You can also replace @latest with the name of your workflow. For eg. in my case the workflow name would be hello-world-xpc6d.

argo list -n argo
argo get -n argo @latest
argo logs -n argo @latest
Enter fullscreen mode Exit fullscreen mode

Output:

hello-world-xpc6d: time="2022-01-18T17:02:54.072Z" level=info msg="capturing logs" argo=true
hello-world-xpc6d:  _____________
hello-world-xpc6d: < hello world >
hello-world-xpc6d:  -------------
hello-world-xpc6d:     \
hello-world-xpc6d:      \
hello-world-xpc6d:       \
hello-world-xpc6d:                     ##        .
hello-world-xpc6d:               ## ## ##       ==
hello-world-xpc6d:            ## ## ## ##      ===
hello-world-xpc6d:        /""""""""""""""""___/ ===
hello-world-xpc6d:   ~~~ {~~ ~~~~ ~~~ ~~~~ ~~ ~ /  ===- ~~~
hello-world-xpc6d:        \______ o          __/
hello-world-xpc6d:         \    \        __/
hello-world-xpc6d:           \____\______/
Enter fullscreen mode Exit fullscreen mode

Congratulations!! 🚀 You successfully ran your first ever simple argo workflow on K3s cluster. I hope this made you curious to explore Argo workflows more deeply.
Checkout this, here you can find different types to workflows and templates that you can try running locally.

Top comments (0)

Read next

arbythecoder profile image

NexaScale Mentorship: A Journey of Growth

Arbythecoder -

viseshagarwal profile image

"Mind Meets Machine: The Evolution of AI through Cognitive Psychology"

Visesh Agarwal -

bnayae profile image

Proactive Architecture Guarding

Bnaya Eshet -

jaber-said profile image

Mastering Git Branching Strategies: Best Practices for Organizing Your Development Workflow

Jaber-Saed -