Yes, you can definitely customize resource requirements per deployment while still inheriting from a base job template! This is achieved using

job_variables

in your deployment configuration. Here's how you can do it: 1. In your base job template (configured in the work pool): Define your common configuration that all deployments will inherit. 2. For each deployment, you can override specific resource settings using

job_variables

. Here's an example:

python
from prefect import flow
from prefect.deployments import Deployment

@flow
def my_resource_intensive_flow():
    # Your flow code here
    pass

deployment = Deployment.build_from_flow(
    flow=my_resource_intensive_flow,
    name="resource-heavy-deployment",
    work_pool_name="my-k8s-pool",
    job_variables={
        "spec": {
            "template": {
                "spec": {
                    "containers": [{
                        "resources": {
                            "requests": {
                                "cpu": "2",
                                "memory": "4Gi"
                            },
                            "limits": {
                                "cpu": "4",
                                "memory": "8Gi"
                            }
                        }
                    }]
                }
            }
        }
    }
)

Alternatively, if you're using

prefect.yaml

, you can specify the job variables there:

yaml
deployments:
  - name: resource-heavy-deployment
    work_pool:
      name: my-k8s-pool
    job_variables:
      spec:
        template:
          spec:
            containers:
              - resources:
                  requests:
                    cpu: "2"
                    memory: "4Gi"
                  limits:
                    cpu: "4"
                    memory: "8Gi"

The

job_variables

will merge with your base job template, overriding only the specific fields you specify while keeping all other configurations from the base template intact. This way, you can: 1. Keep your common configurations (like image, pull secrets, volumes, etc.) in the base template 2. Override only the resource specifications for deployments that need different resources 3. Avoid duplicating the entire job template This approach is particularly efficient because: - It maintains DRY (Don't Repeat Yourself) principles - Makes it easier to manage and update common configurations - Allows for flexible resource allocation per deployment - Keeps your deployment configurations clean and focused on just the differences For more detailed information, you can refer to the Prefect Kubernetes documentation and how to customize job variables. Let me know if you need any clarification or have questions about implementing this in your specific environment!