Deploy the dataplane

If you have not yet set up the required CoreWeave resources (CKS cluster, AI Object Storage bucket, access keys, access policy), see Prepare infrastructure first.

Assumptions

You have a Union.ai organization, and you know the control plane URL for your organization.
You have a cluster name provided by or coordinated with Union.
You have a CKS cluster running one of the most recent three minor Kubernetes versions. Learn more
You have a CoreWeave AI Object Storage bucket, access keys, and access policy as described in Prepare infrastructure.

Prerequisites

Install Helm 3.
Install uctl.
Install the flyte CLI (used later to run a sample workflow).

Deploy the Union.ai operator

Set your KUBECONFIG to the CKS cluster where you want to deploy the data plane:
```
export KUBECONFIG=<PATH_TO_KUBECONFIG>
```
Configure the Union CLI and provision data plane resources:
```
uctl config init --host=<ORG_NAME>.union.ai
uctl selfserve provision-dataplane-resources --clusterName <CLUSTER_NAME> --provider metal
```
- The command will output the ID, name, and a secret that will be used by the Union services to communicate with your control plane. It will also generate a YAML values file specific to the metal provider.
- Save the secret that is displayed. Union does not store the credentials; rerunning the same command can be used to retrieve the secret later.

Update the generated values file with your CoreWeave-specific storage configuration. AI Object Storage requires virtual-hosted style S3 URLs, so you must override the default storage configuration. Replace the placeholders with your actual credentials and settings.

        
    
host: <ORG_NAME>.union.ai
clusterName: <CLUSTER_NAME>
orgName: <ORG_NAME>
provider: metal

storage:
  provider: custom
  bucketName: <BUCKET_NAME>
  fastRegistrationBucketName: <BUCKET_NAME>
  custom:
    type: stow
    container: <BUCKET_NAME>
    stow:
      kind: s3
      config:
        region: <AVAILABILITY_ZONE>
        auth_type: accesskey
        access_key_id: <ACCESS_KEY_ID>
        secret_key: <SECRET_ACCESS_KEY>
        endpoint: https://cwobject.com
        disable_ssl: false
        disable_force_path_style: true

executor:
  extraEnvVars:
    - name: FLYTE_AWS_S3_ADDRESSING_STYLE
      value: "virtual"
    - name: FLYTE_AWS_ENDPOINT
      value: "https://cwobject.com"
    - name: AWS_ACCESS_KEY_ID
      value: <ACCESS_KEY_ID>
    - name: AWS_SECRET_ACCESS_KEY
      value: <SECRET_ACCESS_KEY>
    - name: AWS_DEFAULT_REGION
      value: <AVAILABILITY_ZONE>

config:
  k8s:
    plugins:
      k8s:
        default-env-vars:
          - FLYTE_AWS_ENDPOINT: https://<BUCKET_NAME>.cwobject.com
          - FLYTE_AWS_S3_ADDRESSING_STYLE: "virtual"
          - AWS_ACCESS_KEY_ID: <ACCESS_KEY_ID>
          - AWS_SECRET_ACCESS_KEY: <SECRET_ACCESS_KEY>
          - AWS_DEFAULT_REGION: <AVAILABILITY_ZONE>

operator:
  enableTunnelService: true

secrets:
  admin:
    create: true
    clientId: <CLIENT_ID>
    clientSecret: <CLIENT_SECRET>

fluentbit:
  enabled: true
  env:
    - name: AWS_ACCESS_KEY_ID
      value: <ACCESS_KEY_ID>
    - name: AWS_SECRET_ACCESS_KEY
      value: <SECRET_ACCESS_KEY>

The uctl selfserve provision-dataplane-resources command in step 2 generates the <CLIENT_ID> and <CLIENT_SECRET> values. Use the values from that command’s output.

The settings below are required for AI Object Storage compatibility:

Setting	Value	Purpose
`storage.custom.stow.config.disable_force_path_style`	`true`	Enables virtual-hosted style S3 URLs.
`storage.custom.stow.config.endpoint`	`https://cwobject.com`	AI Object Storage endpoint for the control plane.
`config.k8s.plugins.k8s.default-env-vars` (entry: `FLYTE_AWS_ENDPOINT`)	`https://<BUCKET_NAME>.cwobject.com`	Bucket-specific endpoint injected into task pods.
`executor.extraEnvVars.FLYTE_AWS_S3_ADDRESSING_STYLE`	`virtual`	Configures the executor to use virtual-hosted style addressing.

Add the Union.ai Helm repo:

        
helm repo add unionai https://unionai.github.io/helm-charts/
helm repo update

Install the Custom Resource Definitions (CRDs):

helm upgrade --install unionai-dataplane-crds unionai/dataplane-crds

Install the data plane. Replace <PATH_TO_VALUES_FILE> with the path to the Helm values file you customized in step 3.

        
    
helm upgrade --install unionai-dataplane unionai/dataplane \
  --namespace union --create-namespace \
  --values <PATH_TO_VALUES_FILE> \
  --timeout 10m

Verify the pods are running:
```
kubectl get pods -n union
```
When the deployment succeeds, all pods show a Running status, including union-operator-proxy, union-operator-buildkit, flytepropeller, and executor.

Verify the cluster is registered with the control plane:

uctl get cluster

The output is similar to the following:

        
NAME               ORG          STATE          HEALTH
union-coreweave    my-org       STATE_ENABLED  HEALTHY

Create an API key for your organization. This is required for v2 workflow executions on the data plane. If you have already created one, rerun the same command to propagate the key to the new cluster:
```
uctl create apikey --keyName EAGER_API_KEY --org <ORG_NAME>
```
If you receive a PermissionDenied error, contact Union.ai support to have the permission enabled for your organization.

Test a workflow

To run a sample workflow, complete the following steps:

Create a Flyte CLI configuration file at the path .flyte/config.yaml in your project directory. Replace <ORG_NAME> and <PROJECT_NAME> with your organization and project identifiers.
```
admin:
  endpoint: dns:///<ORG_NAME>.union.ai
image:
  builder: remote
task:
  domain: development
  org: <ORG_NAME>
  project: <PROJECT_NAME>
```
Run a sample workflow:
```
flyte run --image ghcr.io/flyteorg/flyte:py3.13-v2.0.2 \
  hello_world.py main --n 5
```
If the remote image builder isn’t enabled for your organization, use the --image flag with a pre-built container image as in the preceding flyte run example.
Check the run status. Replace <RUN_NAME> with the workflow run identifier.
```
flyte get run <RUN_NAME>
```
Look for ACTION_PHASE_SUCCEEDED in the output to confirm the workflow completed successfully.

Troubleshooting

Symptom	Cause	Fix
`PathStyleRequestNotAllowed 400`	The control plane generates path-style S3 URLs.	Set `storage.custom.stow.config.disable_force_path_style` to `true` in the Helm values file.
`403 Forbidden` on S3 operations	No access policy for the storage key.	Create an object storage access policy in the Cloud Console.
Task pods reach `s3.us-east-1.amazonaws.com`	Task pods are missing the CoreWeave endpoint.	Add `FLYTE_AWS_ENDPOINT` to `config.k8s.plugins.k8s.default-env-vars` with the value `https://<BUCKET_NAME>.cwobject.com`.
“All enabled clusters are unhealthy”	The control plane can’t reach the data plane.	Verify the tunnel service is running: `kubectl get pods -n union \| grep proxy`.
“Remote image builder is not enabled”	The remote builder isn’t enabled on the control plane.	Contact Union.ai to enable the remote builder, or use `--image` with a pre-built image.
`invalid keys: collectbillableresourceusage`	Chart version mismatch with the operator.	Use matching chart and operator image versions.
Helm “another operation in progress”	An interrupted Helm upgrade.	Run `helm rollback unionai-dataplane <LAST_GOOD_REVISION> -n union`.
“Provided Tunnel token is not valid”	The control plane isn’t configured for this cluster.	Complete cluster registration first.

Additional resources

For more information, see the following resources: