@Marvin Using prefect 3 I'd like to add volumemounts to the flow job template using the .deploy() function. Is this possible out of the box? Or would I need to add a variable in the work pool setup and add the volumemmounts there to the base job template, because I don't see it in the setup there. Below follows the standard base job template defined in my work pool.

"job_configuration": {
    "env": "{{ env }}",
    "name": "{{ name }}",
    "labels": "{{ labels }}",
    "command": "{{ command }}",
    "namespace": "{{ namespace }}",
    "job_manifest": {
      "kind": "Job",
      "spec": {
        "template": {
          "spec": {
            "containers": [
              {
                "env": "{{ env }}",
                "args": "{{ command }}",
                "name": "prefect-job",
                "image": "{{ image }}",
                "imagePullPolicy": "{{ image_pull_policy }}"
              }

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Using prefect 3 I'd like to add volumemounts to the flow job template using the .deploy() function. Is this possible out of the box? Or would I need to add a variable in the work pool setup and add the volumemmounts there to the base job template, because I don't see it in the setup there. Below follows the standard base job template defined in my work pool.

``` "job_configuration": { "env": "{{ env }}", "name": "{{ name }}", "labels": "{{ labels }}", "command": "{{ command }}", "namespace": "{{ namespace }}", "job_manifest": { "kind": "Job", "spec": { "template": { "spec": { "containers": [ { "env": "{{ env }}", "args": "{{ command }}", "name": "prefect-job", "image": "{{ image }}", "imagePullPolicy": "{{ image_pull_policy }}" } ], "completions": 1, "parallelism": 1, "restartPolicy": "Never", "serviceAccountName": "{{ service_account_name }}" } }, "backoffLimit": 0, "ttlSecondsAfterFinished": "{{ finished_job_ttl }}" }, "metadata": { "labels": "{{ labels }}", "namespace": "{{ namespace }}", "generate

@Marvin I am using the .deploy() function. Please provide me with an example of how I add the volumes and volumemounts to the work pool JSON Base job Template and also how I should use the .deploy() function to add volumes and volumemounts from the flow itself. Be clear on the syntax in the flow.py that is required for the volumes and volumemounts to be passed on to the base job template.

To configure volume mounts for a flow running in Prefect 3 using the

.deploy()

function, you'll need to adjust your work pool's base job template and include the appropriate details when you deploy. Here's a step-by-step example: ### Step 1: Modify the Base Job Template You'll need to add placeholders for volumes and volume mounts in your work pool's base job template. Here's an example JSON configuration for the job template:

json
{
  "job_configuration": {
    "env": "{{ env }}",
    "name": "{{ name }}",
    "labels": "{{ labels }}",
    "command": "{{ command }}",
    "namespace": "{{ namespace }}",
    "job_manifest": {
      "kind": "Job",
      "spec": {
        "template": {
          "spec": {
            "containers": [
              {
                "env": "{{ env }}",
                "args": "{{ command }}",
                "name": "prefect-job",
                "image": "{{ image }}",
                "imagePullPolicy": "{{ image_pull_policy }}",
                "volumeMounts": "{{ volume_mounts }}"
              }
            ],
            "volumes": "{{ volumes }}"
          }
        }
      }
    }
  }
}

### Step 2: Deploy the Flow with Volume Configurations You can then use the

.deploy()

method in your

flow.py

to specify the volumes and volume mounts. Here's an example of how you might set this up:

python
from prefect import flow

@flow
def my_flow():
    # Your flow logic here
    pass

if __name__ == "__main__":
    my_flow.deploy(
        name="my-flow-with-volumes",
        work_pool_name="my-work-pool",
        job_variables={
            "volumes": [
                {
                    "name": "my-volume",
                    "persistentVolumeClaim": {
                        "claimName": "my-pvc"
                    }
                }
            ],
            "volume_mounts": [
                {
                    "mountPath": "/mnt/data",
                    "name": "my-volume"
                }
            ]
        }
    )

### Explanation - volumes: This specifies the volumes to be used in the flow run. In this example, it's configured to use a PersistentVolumeClaim (PVC). - volumeMounts: This defines how the volumes should be mounted onto the containers. ### Additional Resources - Work Pools in Prefect 3 - Prefect YAML and Job Variables This approach allows you to keep your infrastructure flexible and your deployment configurations clear. Let me know if you have any further questions!

@Marvin I tried to follow your steps. Maybe something is wrong in the formatting of my volumes and volumemounts variables? prefect.exceptions.PrefectHTTPStatusError: Client error '422 Unprocessable Entity' for url 'http://localhost:58265/api/deployments/' Response: {'detail': "Error creating deployment: Validation failed for field 'volumes'. Failure reason: [{'name': 'postgres-exporter', 'secret': {'secretName': 'postgres-exportes'}}, {'name': 'gitea', 'secret': {'secretName': 'gitea-acc'}}, {'name': 'databricks', 'secret': {'secretName': 'azure-service-s'}}, {'name': 'prefect-sp', 'secret': {'secretName': 'azure-service'}}] is not valid under any of the given schemas"} Also can you add the part in the base job template where you declare the variables of volumes and volumemounts and declare their types?

To resolve the issue you're encountering with the deployment, you need to ensure that your

volumes

and

volumeMounts

are correctly formatted according to the JSON schema expected by Prefect. Let's refine the configuration and clarify how to declare these variables in the base job template. ### Correct Formatting for

volumes

and

volumeMounts

Ensure that your definitions follow the expected Kubernetes format. Here's a refined example:

python
# In your flow.py or where you are deploying the flow

my_flow.deploy(
    name="my-flow-with-volumes",
    work_pool_name="my-work-pool",
    job_variables={
        "volumes": [
            {
                "name": "postgres-exporter",
                "secret": {
                    "secretName": "postgres-exporter"
                }
            },
            {
                "name": "gitea",
                "secret": {
                    "secretName": "gitea-acc"
                }
            },
            {
                "name": "databricks",
                "secret": {
                    "secretName": "azure-service-s"
                }
            },
            {
                "name": "prefect-sp",
                "secret": {
                    "secretName": "azure-service"
                }
            }
        ],
        "volume_mounts": [
            {
                "mountPath": "/mnt/data",
                "name": "postgres-exporter"
            },
            {
                "mountPath": "/mnt/gitea",
                "name": "gitea"
            },
            {
                "mountPath": "/mnt/databricks",
                "name": "databricks"
            },
            {
                "mountPath": "/mnt/prefect",
                "name": "prefect-sp"
            }
        ]
    }
)

### Modify the Base Job Template JSON Add placeholders for the variables in your work pool's base job template. Below is an updated JSON with clear declarations for the variables linked to volume configuration:

json
{
  "job_configuration": {
    "env": "{{ env }}",
    "name": "{{ name }}",
    "labels": "{{ labels }}",
    "command": "{{ command }}",
    "namespace": "{{ namespace }}",
    "job_manifest": {
      "kind": "Job",
      "spec": {
        "template": {
          "spec": {
            "containers": [
              {
                "env": "{{ env }}",
                "args": "{{ command }}",
                "name": "prefect-job",
                "image": "{{ image }}",
                "imagePullPolicy": "{{ image_pull_policy }}",
                "volumeMounts": "{{ volume_mounts }}"
              }
            ],
            "volumes": "{{ volumes }}"
          }
        }
      }
    }
  },
  "variables": {
    "volume_mounts": {
      "type": "array",
      "description": "List of volume mounts for the job",
      "items": {
        "type": "object",
        "properties": {
          "mountPath": {"type": "string"},
          "name": {"type": "string"}
        }
      }
    },
    "volumes": {
      "type": "array",
      "description": "List of volumes for the job",
      "items": {
        "type": "object",
        "properties": {
          "name": {"type": "string"},
          "secret": {
            "type": "object",
            "properties": {
              "secretName": {"type": "string"}
            }
          }
        }
      }
    }
  }
}

### Explanation - Variables Section: It defines the schema for

volumes

and

volumeMounts

as arrays of objects, each with specific property types. This helps Prefect validate the configuration against its expectations. - Job Variables in Deployment: When deploying, ensure the

job_variables

match this schema. By correctly declaring these variables and types, you align with Prefect's expected schema, reducing the risk of validation errors. If issues persist, verify the integration with the Kubernetes setup or any secret-related configurations.