Based on my research, I can provide you with the correct syntax for adding extra volumes and volume mounts in your Kubernetes worker's values.yaml file. Here's how you can configure it:

yaml
# values.yaml
worker:
  extraVolumes:
    - name: my-volume
      persistentVolumeClaim:
        claimName: my-pvc
      # Or any other volume type supported by Kubernetes
      
  extraVolumeMounts:
    - name: my-volume
      mountPath: /path/in/container
      readOnly: false  # optional

Key points to note: 1. The

extraVolumes

section follows the standard Kubernetes volume specification format 2. The

extraVolumeMounts

section follows the standard Kubernetes volumeMount specification 3. The

name

in

extraVolumeMounts

must match the corresponding volume name in

extraVolumes

You can use any valid Kubernetes volume type in the

extraVolumes

section, such as: - persistentVolumeClaim - configMap - secret - hostPath - emptyDir Example with multiple volumes:

yaml
worker:
  extraVolumes:
    - name: config-volume
      configMap:
        name: my-config
    - name: data-volume
      persistentVolumeClaim:
        claimName: data-pvc
        
  extraVolumeMounts:
    - name: config-volume
      mountPath: /etc/config
      readOnly: true
    - name: data-volume
      mountPath: /data

These volumes will be mounted in all pods created by the worker. Make sure that any PersistentVolumeClaims or ConfigMaps referenced in your configuration exist in the cluster before deploying the worker. Would you like me to provide examples for any specific type of volume you're trying to mount?

To fix your volume mounting issue, you need to: 1. Create a base job template JSON file that includes your volume configuration:

json
{
    "spec": {
        "volumes": [
            {
                "name": "my-volume",
                "persistentVolumeClaim": {
                    "claimName": "my-pvc"
                }
            }
        ],
        "containers": [
            {
                "name": "prefect-job",
                "volumeMounts": [
                    {
                        "name": "my-volume",
                        "mountPath": "/path/in/container"
                    }
                ]
            }
        ]
    }
}

2. Create or update your work pool with this configuration:

bash
prefect work-pool create "my-pool" \
    --type kubernetes \
    --base-job-template path/to/your/template.json

Or if you're using the UI, you can paste the JSON configuration in the "Base Job Template" section when creating/editing the work pool. The key difference is: - Worker values.yaml: Configures the worker deployment itself - Work pool configuration: Configures how the flow run pods are created This is why you see the volume configuration being accepted in the helm deployment (it's valid YAML) but not appearing in your flow run pods (because it's not in the work pool configuration where the flow run pods get their configuration). Would you like me to provide more specific examples for your particular volume configuration? Or would you like to see how to verify that your work pool configuration is correctly set up?

Now I can explain why the values.yaml approach doesn't work: 1. Architectural Separation: - The worker itself is just a lightweight service that polls for work and creates pods - The worker pod (configured by values.yaml) and the flow run pods are completely separate entities - Think of the worker as a "manager" that creates and oversees the actual "worker" pods that run your flows 2. Configuration Inheritance: - Configurations in values.yaml ONLY affect the worker pod itself - The worker pod doesn't "share" or "inherit" its configuration with the flow run pods it creates - Flow run pods are created fresh each time using the work pool's base job template Here's a visual representation:

values.yaml configuration
        ↓
    Worker Pod
        ↓
Creates Flow Run Pods → Uses Work Pool Configuration
                         (base job template)

3. Why This Design Makes Sense: - Isolation: Each flow run gets a clean, isolated environment - Flexibility: Different flows in the same work pool can have different configurations - Security: The worker pod (which has permissions to create other pods) can have different security contexts than the flow run pods 4. Correct Configuration Locations: - Use values.yaml for: Worker pod configuration, worker resources, worker security context - Use work pool configuration for: Flow run pod configurations, volume mounts, environment variables, resource requests This is why your volume mounts started working when you moved them to the work pool configuration - you were putting the configuration where the flow run pods actually look for it, rather than in the worker pod's configuration which doesn't get propagated. Think of it like a hotel: the hotel manager (worker) doesn't share their office configuration with each guest room (flow run pods). Instead, each room is set up according to a room template (work pool configuration). Would you like me to explain any specific aspect of this architecture in more detail?