Getting started
This page takes you from an empty canvas to real Argo Workflows YAML you own. No cluster and no execution required to get there. When you want dagweave to run the workflow for you, the last section covers that too.
dagweave is the visual editor for Argo Workflows. You build a pipeline as a graph and it writes the YAML for you, so you do not have to memorise the Argo Workflows schema to get a working manifest.
Two ways to use dagweave
Section titled “Two ways to use dagweave”dagweave splits into two roles, and which one you are decides where you start:
- Workflow authors build workflows on the canvas. This is most people. You do not need to touch Kubernetes or install anything to author a workflow and take its YAML.
- Cluster operators install the connector once so authors can run their workflows on your Argo Workflows cluster. You only do this if your team wants dagweave to submit runs.
If you are here to build workflows, keep reading. If you are here to connect a cluster, jump to Installing the connector.
Open the builder
Section titled “Open the builder”The builder runs in your browser. There is no CLI to install and no local dependency to set up. Sign in and you land on an empty canvas with the node palette on the side.
Build your first workflow
Section titled “Build your first workflow”- Add a node to the canvas from the palette. Each node is one step in your pipeline.
- Set its container image and the command it runs.
- Add a second node and draw an edge from the first to it. The edge is a dependency: the second step waits for the first. You can also wire an output of one step into an input of the next, so data flows down the graph.
- Open Settings and pick the kind you want to produce: WorkflowTemplate, Workflow, or CronWorkflow.
- Watch the YAML preview update as you go. When it looks right, copy it or download the file.
That YAML is real Argo Workflows, and it is yours. Apply it the same way you would a manifest you wrote by hand:
kubectl apply -f my-pipeline.yaml# or, for a one-off runargo submit my-pipeline.yamlThis is the free path start to finish: build visually, get real YAML, take it to your own cluster. You never have to hand dagweave your cluster to get value from it.
The node palette
Section titled “The node palette”dagweave ships a set of core nodes that map to common pipeline steps. You wire them together instead of writing container templates by hand:
- run-script runs an inline script in a container.
- run-container runs a prebuilt image with your command and args.
- http-request calls an HTTP endpoint.
- k8s-resource creates or patches a Kubernetes resource.
- approval pauses the run and waits for a human to resume it.
Every node has a config form driven by its schema, so you fill in fields instead
of guessing at YAML keys. You can also add global parameters and reference them
with {{workflow.parameters.x}} in any field, and repeat a node over a list to
fan out work.
Git checkout and commit-push are not core nodes any more. They come from the catalog as versioned, reusable templates, along with the ContainerSet and plugin wrappers. See the node reference for every type.
Run it on your cluster
Section titled “Run it on your cluster”Copying YAML is enough if you drive Argo Workflows yourself. If you want dagweave to submit runs and show you the results, a cluster operator installs the connector on your cluster. It opens a single outbound channel to dagweave, so your cluster never accepts inbound traffic. See Installing the connector.
Once a cluster is connected you can attach triggers to a workflow (a button, a cron schedule, a webhook, or an event) and watch each run in the executions view with logs, metrics, and re-run.
Next steps
Section titled “Next steps”- Core concepts explains how the canvas compiles, how you wire data between steps, and how import round-trips your existing YAML.
- Installing the connector connects your Argo Workflows to dagweave.
- Triggers covers manual, cron, webhook, and event runs.
- Executions covers watching runs and reading logs.