Evaluate Pipekit Cloud

Sign up for Pipekit Cloud, get a free-trial cluster, and run your first workflow in 5 minutes.

A linear 5-minute path from "I want to try Pipekit" to "my first workflow is running."

This quickstart uses the free-trial cluster Pipekit provisions for new accounts. If you'd rather use your own cluster, follow Operate Pipekit instead.

Prerequisites

• A computer running macOS, Linux, or Windows (for the CLI).

• A browser (for the UI).

1. Create an account

1. Go to https://pipekit.io and click Get started free.

2. Complete the signup form, or use SSO.

3. Check your email for the welcome message and click the confirmation link.

4. Log in.

2. Create an Organization

Pipekit will take you to the Org page on first login.

1. Click Create an Org.

2. Give the Organization a name and description.

3. Click Submit.

3. Provision the free-trial cluster

When prompted to connect a cluster, confirm that you want a Pipekit-hosted free-trial cluster. Provisioning takes 2 to 3 minutes; you'll be redirected to the Pipes page when it's ready.

The free-trial cluster comes pre-configured with Argo Workflows, the Pipekit Agent, and a working MinIO artifact store. For its limits and configuration, see Free Trial Cluster.

4. Install the CLI

# macOS / Linux (Homebrew)
brew install pipekit/tap/cli

# Windows (Scoop)
scoop bucket add pipekit https://github.com/pipekit/scoop.git
scoop install pipekit/cli

For other install methods (NixOS, Docker), see Reference > CLI > Install.

5. Log in from the CLI

pipekit login

Follow the prompts to authenticate against the same account you created in step 1.

6. Submit your first workflow

Use the Pipekit Examples repository for a tested sample workflow:

git clone https://github.com/pipekit/examples.git
cd examples
pipekit submit --cluster-name=<your-free-trial-cluster-name> examples/dag-diamond/workflow.yaml

Pipekit creates a Pipe named after the workflow's generateName and submits a Run. The CLI prints a link to the Run in the UI.

7. View the Run

Open the link from step 6 (or go to https://pipekit.io/pipes). You'll see:

• The Run Graph: a DAG view of the workflow's tasks.

• Pod Logs per container, with level detection and search.

• The submitted YAML.

What's next

• Trigger Workflows from Git instead of the CLI: Pipes covers GitHub, GitLab, and Bitbucket integration.

• Schedule Workflows: see Cron.

• Author with Python: see Reference > Python SDK (works with Hera).

• Add your own cluster alongside the free trial: Operate Pipekit.

• Set up access control before inviting teammates: Access Control.

Best practice

Set a namespace and serviceAccountName on your workflows. The Pipekit Examples workflows use namespace: argo and serviceAccountName: argo-workflow, which match the free-trial cluster's configuration. If you submit a workflow without these set, Pipekit submits to default and your workflow will likely fail with permission errors.