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Controller Installation

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

This will create a new namespace, argo-rollouts, where Argo Rollouts controller will run.


If you are using another namspace name, please update install.yaml clusterrolebinding's serviceaccount namespace name.


When installing Argo Rollouts on Kubernetes v1.14 or lower, the CRD manifests must be kubectl applied with the --validate=false option. This is caused by use of new CRD fields introduced in v1.15, which are rejected by default in lower API servers.


On GKE, you will need grant your account the ability to create new cluster roles:

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

You can find released container images of the controller at There are also old releases at Dockerhub, but since the introduction of rate limiting, the Argo project has moved to Quay.

Kubectl Plugin Installation

The kubectl plugin is optional, but is convenient for managing and visualizing rollouts from the command line.


brew install argoproj/tap/kubectl-argo-rollouts


  1. Install Argo Rollouts Kubectl plugin with curl.

    curl -LO

    For Linux dist, replace darwin with linux

  2. Make the kubectl-argo-rollouts binary executable.

    chmod +x ./kubectl-argo-rollouts-darwin-amd64
  3. Move the binary into your PATH.

    sudo mv ./kubectl-argo-rollouts-darwin-amd64 /usr/local/bin/kubectl-argo-rollouts

Test to ensure the version you installed is up-to-date:

kubectl argo rollouts version

Shell auto completion

The CLI can export shell completion code for several shells.

For bash, ensure you have bash completions installed and enabled. To access completions in your current shell, run $ source <(kubectl-argo-rollouts completion bash). Alternatively, write it to a file and source in .bash_profile.

The completion command supports bash, zsh, fish and powershell.

See the completion command documentation for more details.

Using the CLI with Docker

The CLI is also available as a container image at

You can run it like any other Docker image or use it in any CI platform that supports Docker images.

docker run version