Connectors

Let your whole team run Argo Workflows.

One helm chart. You install it once. After that, anyone with a dagweave account can run Argo Workflows, not just you.

The problem

You already run Argo Workflows. Most of your team still cannot use it.

You run the cluster and you paid for the expertise. Using it means hand-writing Workflow YAML. That keeps it with the handful of people who can.

dagweave lets your whole team build workflows. The connector dispatches them to the cluster you already paid for.

Enrollment

One connector per cluster

dagweave generates the command, enrollment token included. The operator installs the chart once per cluster, then names each Argo Workflows instance the connector should manage.

Your cluster credentials stay in your cluster. dagweave never holds a kubeconfig.
The connector opens every connection outbound. Nothing needs an inbound port.
The connection names the Argo Workflows and Kubernetes versions it found. A control your cluster cannot honour says so on the step, rather than going quiet.

High availability

Survives a node drain

It ships production-ready, and there is nothing to tune.

the chart's defaults, none of them yours to setyaml

replicaCount: 2
leaderElection:
  enabled: true            # one replica acts, the other waits
podDisruptionBudget:
  enabled: true            # a drain cannot take both at once
  maxUnavailable: 1
topologySpreadConstraints:
  enabled: true
  zone: true               # topology.kubernetes.io/zone
  hostname: true           # kubernetes.io/hostname
  whenUnsatisfiable: ScheduleAnyway
podAntiAffinity:
  enabled: true
  type: soft               # so one node can still schedule both

What lands in the cluster

The log collector

A step fails and you want its log. A stock install brings the collector. Point it at S3, or let dagweave store your logs, and each one lands on the step.

Logs go to the console by default. Send them to your own S3, Loki or HTTP endpoint and dagweave never sees them.
Or let dagweave store them for you. With S3 or dagweave, each log lands on the step that produced it.
The collector only reads pods Argo Workflows labelled, nothing else on the node.

Dispatch

Your workflows run on your cluster

The connector holds an outbound stream open. dagweave sends the compiled manifest over it, your Argo Workflows instance runs the workflow, and status comes back on the same stream. Nothing runs in dagweave.

Every dispatch is a fresh Workflow with its own generated name and dagweave's ids on its pods.

enroll and dispatchtext

helm install  ->  operator enrolls the connector, once
dispatch      ->  Workflow / WorkflowTemplate / CronWorkflow
report        ->  phase, per-step status, log refs, artifact URLs

Roles

Authors trigger runs without cluster access

The operator holds the cluster credentials and installs the connector. After that, the people who build workflows dispatch runs on a dagweave permission alone.

No kubeconfig, no cluster RBAC.
The operator keeps control of what the connector can reach, in the cluster.
When a dispatch does not arrive, the connector's own logs are in dagweave. No kubectl needed to find out why.

Connect the cluster you already have.

dagweave is in early access. Leave an email and we will bring you on as we open it up.