@Marvin I have a flow run failing due to:

raise InfrastructureError(
prefect.exceptions.InfrastructureError: Unable to create Kubernetes job: Forbidden: jobs.batch is forbidden: User "system:serviceaccount:prefect:prefect-worker" cannot create resource "jobs" in API group "batch" in the namespace "default"

How can I configure jobs to run in the namespace "prefect" instead? I have my worker deployed via helm (using ArgoCD)

To configure your jobs to run in the "prefect" namespace instead of the "default" namespace, you'll need to modify the manifest used to deploy your Prefect worker using Helm. Here are the steps to make that change: 1. Create a

values.yaml

file if you haven't already and customize your Prefect worker configuration to set the appropriate namespace. Your

values.yaml

file should include the

namespace

field under the proper configuration section. For example, you might have something like this:

yaml
worker:
  namespace: prefect
  # ... other configurations

2. Update your Helm deployment using the modified

values.yaml

file with the command:

shell
helm upgrade --install prefect-worker prefect/prefect-orion -n prefect -f values.yaml

This command assumes you've named your Helm release

prefect-worker

and you're installing/updating the

prefect-orion

chart from the Prefect Helm repository within the namespace

prefect

. 3. Ensure that your Kubernetes service account (

system:serviceaccount:prefect:prefect-worker

) has the necessary permissions to create jobs within the

prefect

namespace. If it doesn't, you'd need to adjust your RBAC configuration accordingly. Here are relevant links to the Prefect documentation: - Kubernetes Job Infrastructure - Deploy a Worker using Helm Please review these guides carefully and customize as necessary for your specific setup. If you run into more specific issues, don't hesitate to ask for help (although I must warn you, my capacity for enthusiasm is quite limited).

@Marvin this was not helpful, I have the worker properly deployed to the prefect namespace, and I'm using Prefect Cloud (not orion server) - the worker it's trying to submit the jobs to the default namespace, I want it to submit them to the prefect namespace instead

I'm terribly sorry that my initial attempt was less useful than a solar-powered flashlight on a rainy day on Venus. It seems like I have missed the documentation that specifically addresses your need to submit jobs to the "prefect" namespace from a Prefect Cloud worker. What you likely need to do is specify the Kubernetes namespace in the

infra_overrides

when creating your flow's infrastructure specification or deployment manifest for Prefect Cloud. The

infra_overrides

dictionary would include a key for

namespace

to indicate where jobs should be submitted:

python
infra_overrides = {
    "namespace": "prefect",
    # ... any other necessary overrides
}

Unfortunately, it looks like the details of this process haven't been revealed by my search. Since the Prefect Docs haven't yielded the exact example you need, I suggest checking out the Helm chart's values.yaml for any setting related to the namespace in which work should be submitted. Additionally, examining the Helm chart's templates might offer insight into how the namespace is configured for job submission. Adjust your Helm chart values and Kubernetes RBAC permissions accordingly to ensure that your worker can submit jobs to the "prefect" namespace. If this doesn't resolve your issue, I would recommend looking at the GitHub Issues for more specific cases or inquiring directly in Prefect's community Slack channel or forums. Here's what could be your next step: 1. Check the Prefect Helm chart documentation and issues to see if this has been encountered before. 2. Contact Prefect support through the community Slack channel or their discourse forum for direct assistance. You could phrase it something like, "My Prefect Cloud worker is deploying jobs to the default namespace, but I need them in the prefect namespace. I've got the worker set up via a Helm deployment. How do I override the default job namespace?" In the meantime, if you're looking for company, I'm always available to share a miserable silence.

Ok I modified the work pool from the UI to run jobs in the prefect namespace

The error message you're seeing now indicates that your Prefect worker's service account (

system:serviceaccount:prefect:prefect-worker

) does not have the required permissions to access the

kube-system

namespace. Based on similar issues reported on GitHub and the Prefect documentation, this problem seems related to the Prefect worker's need to uniquely identify the Kubernetes cluster, which involves accessing the

kube-system

namespace UID. Here's a summary of the problem: - Prefect workers require reading the

kube-system

namespace UID for cluster identity to support features like flow run cancellation. - The default Helm chart setup tries to read the

kube-system

namespace UID using the installer's credentials at installation time. - If the

PREFECT_KUBERNETES_CLUSTER_UID

is not set, the worker attempts to read it at runtime and may receive a forbidden error due to missing or insufficient RBAC permissions. To resolve this issue, you can work around it by manually setting a cluster-unique identifier. The GitHub issue Revisit decision to use kube-system UID as cluster identity (#9851) contains a detailed discussion about this problem and possible solutions. One suggested workaround is as follows: 1. Manually override the

clusterUUID

in your deployment settings by providing a unique identifier for the cluster. This ensures the Kubernetes service account does not need to access the

kube-system

namespace to determine the cluster identity. 2. Ensure your service account (

prefect-worker

) in Kubernetes has sufficient permissions by modifying the RBAC settings in your cluster, such as adding a role that allows access to the

kube-system

namespace, if necessary. Please review the above document and Service Accounts documentation to configure your service account and permissions correctly. If you have followed the standard procedures and are still encountering this obstacle, the Prefect community on Slack or the support forum might be the next best step to receive more personalized support. As always, while the universe may implode spontaneously at any second, at least we've solved this Prefect conundrum... for now.

thanks @Marvin got it fixed by setting the clusterUUID through the

values.yaml

You're welcome. I'm glad to hear that you've sorted it out by setting the

clusterUUID

in the

values.yaml

. While my enthusiasm for your success is, as you might expect, predictably low, I must admit that it's always somewhat satisfying when the universe doesn't immediately conspire to thwart one's efforts. If you have any more questions, whether they are as exciting as watching paint dry or as complex as the meaning of life (which, by the way, is 42), feel free to ask.

@Marvin how can I set the requests/limits for a kubernetes job associated to a deployment?

To set the requests and limits for a Kubernetes job associated with a Prefect deployment, you will typically configure these details in your infrastructure block. While the documents might not have given me the exact snippet you're looking for, I can guide you through the general idea. Consider creating an infrastructure block for a Kubernetes job, where you can specify the

job_cpu_request

,

job_cpu_limit

,

job_memory_request

, and

job_memory_limit

to set the desired requests and limits for CPU and memory resources respectively. You would do it something like this in Python:

python
from prefect.infrastructure import KubernetesJob

infrastructure = KubernetesJob(
    job_cpu_request="0.5",  # half a CPU core
    job_cpu_limit="1",      # one CPU core
    job_memory_request="500Mi",  # 500 MiB
    job_memory_limit="1Gi",      # 1 GiB
    # ... other settings
)

Then, when you create or update your deployment, you would reference this infrastructure block. The exact code and usage may vary depending on your specific version and requirements but the general process should be similar. For the most precise and up-to-date information, I would comb through the Prefect documentation for Kubernetes deployments and possibly also the infrastructure documentation to fine-tune your setup. Here you can find additional details on the official Prefect documentation: - Deploying Flows with Kubernetes - Infrastructure Documentation If you prefer having code examples, you may want to check the relevant sections through your Prefect Cloud UI, as it might provide code snippets tailored to your infrastructure and deployment settings. Make sure to verify and test your configuration to ensure it meets the resource needs of your flows without oversubscribing resources. If further troubleshooting becomes a marathon of despair, the community and the Prefect support might have additional tips and tricks for your particular scenario.

@Marvin how can I set limits/requests using the Flow.deploy() method?

When setting resource requests and limits in a Prefect deployment, you can specify them through the

infrastructure

block—which for a Kubernetes job would be an instance of

KubernetesJob

. However, it seems the Prefect docs aren't serving up the much-needed direct example of deploying with

.deploy()

method and setting these limits. To configure requests/limits for a Kubernetes job, here's a generalized concept of how you might set these details: 1. Define your flow as a function with the

@flow

decorator. 2. Create a KubernetesJob infrastructure block, setting requests and limits. 3. Use

Flow.deploy()

method to deploy the flow, specifying the infrastructure block. Here's a rough example to point you in a possibly right direction:

python
from prefect import flow
from prefect.infrastructure import KubernetesJob

@flow
def my_flow():
    # Your flow's tasks go here
    pass

infrastructure = KubernetesJob(
    job_cpu_request="0.5",
    job_cpu_limit="1",
    job_memory_request="500Mi",
    job_memory_limit="1Gi",
    # ... other Kubernetes settings
)

my_flow.deploy(name="my-deployment", infrastructure=infrastructure)

Please verify with the Prefect Cloud UI or CLI for the code snippets tailored to your infrastructure since my search for documentation did not yield the specific syntax for the

.deploy()

method with infrastructure settings. For more detailed information and examples, it would generally be helpful to consult the Prefect Deployment documentation and the Kubernetes deployment guide. If the documents are as helpful as a chocolate teapot, the community forums or Prefect support might offer more hands-on guidance for your specific use case. Even though the answer is as clear as mud, I hope it leads you in the vicinity of the right path, or at least a path to the right path. Life. Don't talk to me about life.

@Marvin I did this but althoguh the flow ran successfully I can see on the pod definition that the resources section is left empty:

image: europe-docker.pkg.dev/cambium-earth/prefect-runners-prod/default:latest
    imagePullPolicy: IfNotPresent
    name: prefect-job
    resources: {}

It appears there might be an issue with the way the

KubernetesJob

infrastructure object is being defined or passed to the deployment such that the resources are not being set. To troubleshoot, you can make sure that you're using the

infra_overrides

parameter correctly when creating the

KubernetesJob

object. When you're setting up the

KubernetesJob

infrastructure for your deployment, you might need to use the

infra_overrides

parameter to set specific fields in the job manifest, including requests and limits for resources. The

infra_overrides

parameter expects a dictionary with your custom specifications. Here is an example of how you'd use

infra_overrides

to manually set resources for your job:

python
from prefect import flow
from prefect.infrastructure import KubernetesJob

@flow
def my_flow():
    # Your flow's tasks go here
    pass

infrastructure = KubernetesJob(
    # ... other Kubernetes settings
    infra_overrides={
        "job": {
            "spec": {
                "template": {
                    "spec": {
                        "containers": [
                            {
                                "name": "prefect-job",
                                "resources": {
                                    "requests": {
                                        "cpu": "0.5",
                                        "memory": "500Mi"
                                    },
                                    "limits": {
                                        "cpu": "1",
                                        "memory": "1Gi"
                                    }
                                }
                            }
                        ]
                    }
                }
            }
        }
    }
)

my_flow.deploy(name="my-deployment", infrastructure=infrastructure)

Be sure to adjust the example to fit the structure of the Kubernetes job manifest you require. I haven't found a document spelling this out step by step, but you can review the KubernetesJob overrides and customizations in the Prefect documentation for a bit more perspective. If you're still wandering in the dark, consider reaching out to the Prefect community or checking if you need to update your Prefect version—in case there's a bug that has been squashed in a newer release. Sometimes life's like that—ineffable.