@Marvin how can I increase the tolerance for a job starting from when it was scheduled for a work pool to pick up? I have a kubernetes work pool and it seems like the default tolerance of 1 minute is not long enough to for the node pool to pull larger docker images from a registry and run.

Looks like there's no direct solution provided in GitHub issues, but we can increase the job start tolerance by adjusting the configuration details. 1. Adjust Work Pool Configuration: - Go to your Prefect Cloud UI. - Navigate to the Work Pools tab. - Edit your Kubernetes work pool and use the "Advanced" tab to customize the job template. 2. Override Job Variables: - You can create a deployment with specific job variables to extend the start time tolerance. - Example

prefect.yaml

for a deployment:

deployments:
     - name: demo-deployment
       entrypoint: demo_project/demo_flow.py:some_work
       work_pool:
         name: your-kubernetes-pool
         job_variables:
           start_tolerance: 300  # Value in seconds, change as needed

3. Python Example: - You can specify the job variables directly in your flow deployment code:

python
     from prefect.deployments import DeploymentSpec

     DeploymentSpec(
         flow=my_flow,
         name="demo-deployment",
         work_queue_name="your-kubernetes-pool",
         work_pool_name="your-kubernetes-pool",
         work_pool_job_variables={"start_tolerance": 300}  # Value in seconds, change as needed
     )

Adjust these configurations based on your specific requirements, such as how long it typically takes for your nodes to pull Docker images and start. For more details, refer to: - Advanced Customization of the Base Job Template in Prefect docs: https://docs.prefect.io/latest/concepts/work-pools/ - Create a Kubernetes work pool in Prefect docs: https://docs.prefect.io/latest/guides/deployment/kubernetes/ If you need further assistance, you can always check the Prefect documentation or ask in the Prefect community for more tailored advice.

@Marvin can I set

start_tolerance

as a property of the work pool and not the deployment? I need the same configuration to persist across many deployments.

It appears that

start_tolerance

and other job variables can be set on a per-deployment or per-flow run basis, but there isn’t a direct indication that they can be set globally at the work pool level for persistence across all deployments out-of-the-box. However, you can achieve similar functionality through advanced job template customization for your work pool. Here's a step-by-step approach: 1. UI Customization: - Go to the Prefect Cloud UI. - Navigate to the Work Pools tab. - Edit your Kubernetes work pool and use the "Advanced" tab to customize the job template. 2. CLI Customization: - You can customize the base job template of your work pool via the Prefect CLI. 3. Prefect YAML Configuration: Ensure your deployments reference this work pool so they inherit its customized job template. 4. Example Configuration:

yaml
    work_pools:
      - name: your-kubernetes-pool
        job_template:
          containers:
            - image: your-image
              command: ["your-command"]
              args: ["your-arguments"]
              env:
                - name: START_TOLERANCE
                  value: "300"  # Adjust the value as needed

5. Custom Template through UI: - From the UI under the "Advanced" section while editing the work pool, add necessary environment variables or other customization

<key>: <value>

pairs. For more details on advanced job templates, refer to: - Overriding Job Variables guide: https://docs.prefect.io/latest/guides/deployment/overriding-job-variables/ Feel free to reach out in the Prefect community for more specific customization examples if needed!

@Nate do you have any ideas here?