Remote Executor Deployment Errors and Configuration

Deploying the Remote Executor encounters errors during setup or configuration, preventing the executor from starting or connecting to the DataHub instance to run ingestion jobs.

Note: For DataHub Cloud customers, infrastructure-level changes are managed by DataHub Support.

1. Review deployment prerequisites:

   • Ensure Kubernetes cluster meets minimum requirements
   • Verify network connectivity to DataHub GMS endpoint
   • Confirm Docker image access and proper image registry credentials

2. Configure Remote Executor:

# executor-values.yaml
datahub:
  gms_url: "https://your-datahub.acryl.io/gms"
  datahub_token: "${DATAHUB_TOKEN}"

executor:
  replicas: 2
  resources:
    requests:
      memory: "2Gi"
      cpu: "1"
    limits:
      memory: "4Gi"
      cpu: "2"

3. Common deployment errors:

   • Image pull errors: Verify credentials for private registry
   • Connection timeout: Check firewall rules and DNS resolution to GMS
   • Authentication failures: Confirm token has proper permissions
   • Crash loop: Review executor pod logs with kubectl logs

4. Debug executor issues:

# Check executor pod status
kubectl get pods -n datahub

# View logs
kubectl logs -f deployment/datahub-remote-executor -n datahub

# Check network connectivity
kubectl exec -it deployment/datahub-remote-executor -n datahub -- curl https://your-datahub.acryl.io/gms/health

5. For cloud customers:
   • Contact support for executor deployment assistance
   • Support can provide correct image versions and configurations
   • May offer managed Remote Executor options

Test configurations in a development environment before applying to production. Always backup configurations before making changes.

• DataHub Documentation
• Remote Executor Setup

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