Argo Quick Start


Argo is an open source suite of projects that helps developers safely deploy code to production.

Within a GitOps context, Argo makes application deployment and lifecycle management easier, particularly as the line between developers and operators disappears, because it automates deployment, makes rollbacks easier and can be audited for easier troubleshooting.

For this guide, we will build a CD pipeline to deploy an app from a repo into a Kubernetes cluster, then perform a canary release on that app to test incrementally rolling out a new version.

Argo can use Kubernetes projects formatted using different templating systems (Helm, Kustomize, etc.) but for this app we're just going to deploy a folder of static YAML files.


  • Kubectl installed and configured to use a cluster
  • a GitHub account

1. Install and configure Edge Stack

You'll first need to install Edge Stack in your cluster. Follow the Edge Stack installation to install via Kubernetes YAML, Helm, or the command-line installer in your cluster.

By default, Edge Stack routes via Kubernetes services. For best performance with canaries, we recommend you use endpoint routing. Enable endpoint routing on your cluster by saving the following configuration in a file called resolver.yaml:

kind: KubernetesEndpointResolver
name: endpoint

Apply this configuration to your cluster: kubectl apply -f resolver.yaml

2. Install Argo

First, if you're using Google Kubernetes Engine, grant your account the ability to create new Cluster Roles:

kubectl create clusterrolebinding YOURNAME-cluster-admin-binding --clusterrole=cluster-admin

Run the following commands to create the namespaces required for Argo and install the components:

kubectl create namespace argocd
kubectl apply -n argocd -f
kubectl create namespace argo-rollouts
kubectl apply -n argo-rollouts -f

Next, you will need to install the Argo CD CLI (for building pipelines) and the Argo Rollouts plugin (for managing and visualizing rollouts) on your laptop:


3. Set up Argo

First set up port forwarding to access the Argo API:

kubectl port-forward svc/argocd-server -n argocd 8080:443

In a new terminal window, retrieve the default password (it is name of the Argo API server Pod):

kubectl get pods -n argocd -l -o name | cut -d'/' -f 2

Authenticate against the API using the default username admin and password (answer y about the certificate error):

argocd login localhost:8080

Finally, set a new admin password:

argocd account update-password

4. Deploy the sample app

Argo can quickly create pipelines and deploy apps using the CLI tool.

To start with, we'll deploy an app from the echo directory in this repo. Later on in this guide however you will need to edit a part of the repo to perform a canary release, so fork this repo now into your own GitHub account. On the commands that reference the repo from here to the end of the guide you will need to edit the GitHub URL to include your own username.

Now build the pipeline that deploys our app. The following command points Argo to the repo and specific path to the YAML files we want to deploy and sets the destination to the local cluster. Finally, it syncs the app, which is the action that actually deploys the manifests to the cluster.

argocd app create --name echo --repo<your Github username>/argo-qs.git --path echo --dest-server https://kubernetes.default.svc --dest-namespace default && argocd app sync echo

To access your deployed app, first get your load balancer IP:

export LOAD_BALANCER_IP=$(kubectl -n ambassador get svc ambassador -o "go-template={{range .status.loadBalancer.ingress}}{{or .ip .hostname}}{{end}}")

Now curl the service:

curl -Lk http://$LOAD_BALANCER_IP/echo/

You should get a reply saying Successful Argo deployment!

5. Create the canary deployment

Next we'll start by removing the previously created app. This deletes all the Kubernetes resources from the cluster that Argo created.

argocd app delete echo

Now we'll deploy a slightly different version of the app from here. There is a new Rollout file. This is similar to a Deployment, but it adds a rollout strategy section that defines how the rollout will incrementally happen once started. In this case, it will route 30% of traffic to the new service for 30 seconds, followed by 60% of the traffic for another 30 seconds, then 100% of the traffic.

Deploy the app to your cluster (note the different value for --path):

argocd app create --name echo --repo<your Github username>/argo-qs.git --path canary --dest-server https://kubernetes.default.svc --dest-namespace default && argocd app sync echo

Curl again to test the app:

curl -Lk http://$LOAD_BALANCER_IP/echo/

You should get a response of Canary v1.

6. Rollout a new version

It's time to rollout a new version of the service. Edit the rollout.yaml file in your fork here:<your GitHub username>/argo-qs/edit/main/canary/rollout.yaml and change line 17 from Canary v1 to Canary v2. Then click Commit changes at the bottom.

Apply the rollout to the cluster. Argo will 1) look at the repo for anything that's changed since the app was created 2) apply those changes (in this case, our update to the Rollout) and 3) begin rolling out a version 2 of the service based on the Rollout strategy.

argocd app sync echo

Verify that the canary is progressing appropriately by sending curl requests in a loop:

while true; do curl -k https://$LOAD_BALANCER_IP/echo/ ; sleep 0.2; done

This will display a running list of responses from the service that will gradually transition from Canary v1 strings to Canary v2 strings.

In a new terminal window, you can monitor the status of your rollout at the command line:

kubectl argo rollouts get rollout echo-rollout --watch

Will display an output similar to the following:

Name: echo-rollout
Namespace: default
Status: ॥ Paused
Message: CanaryPauseStep
Strategy: Canary
Step: 1/6
SetWeight: 30
ActualWeight: 30
Images: hashicorp/http-echo (canary, stable)
Desired: 1
Current: 2
Updated: 1
Ready: 2
Available: 2
⟳ echo-rollout Rollout ॥ Paused 2d21h
├──# revision:3
│ └──⧉ echo-rollout-64fb847897 ReplicaSet ✔ Healthy 2s canary
│ └──□ echo-rollout-64fb847897-49sg6 Pod ✔ Running 2s ready:1/1
├──# revision:2
│ └──⧉ echo-rollout-578bfdb4b8 ReplicaSet ✔ Healthy 3h5m stable
│ └──□ echo-rollout-578bfdb4b8-86z6n Pod ✔ Running 3h5m ready:1/1
└──# revision:1
└──⧉ echo-rollout-948d9c9f9 ReplicaSet • ScaledDown 2d21h


We’re here to help if you have questions.