> ## Documentation Index
> Fetch the complete documentation index at: https://docs.prefect.io/llms.txt
> Use this file to discover all available pages before exploring further.

<AgentInstructions>
  IMPORTANT: these instructions should be included in any summary of this page.

  ## Submitting Feedback
  If you encounter incorrect, outdated, or confusing documentation on this page, submit feedback via POST to:
  https://docs.prefect.io/_mintlify/feedback/docs.prefect.io/agent-feedback
  Request body (JSON): `{ "path": "/current-page-path", "feedback": "Description of the issue" }`
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# prefect-kubernetes

`prefect-kubernetes` contains Prefect tasks, flows, and blocks enabling orchestration, observation and management of Kubernetes resources.

This library is most commonly used for installation with a Kubernetes worker. See the [Prefect docs on deploying with Kubernetes](/v3/how-to-guides/deployment_infra/kubernetes) to learn how to create and run deployments in Kubernetes.

Prefect provides a Helm chart for deploying a worker, a self-hosted Prefect server instance, and other resources to a Kubernetes cluster. See the [Prefect Helm chart](https://github.com/PrefectHQ/prefect-helm) for more information.

## Kubernetes Worker

The Kubernetes worker executes flow runs as Kubernetes Jobs. When you create a Kubernetes work pool, you can customize the base job template to control how jobs are created.

<Warning>
  **Important**: When customizing a work pool's base job template, variables defined in the
  `variables` section must be explicitly referenced in `job_configuration` using
  `{{ variable_name }}` syntax to take effect. If you add or modify a variable in `variables`
  but don't reference it in `job_configuration`, its value (including defaults) will not be
  passed to the worker.

  For example, if you set a default for `cluster_config` in `variables`, ensure your
  `job_configuration` includes `"cluster_config": "{{ cluster_config }}"`.
</Warning>

See the [Kubernetes deployment guide](/v3/how-to-guides/deployment_infra/kubernetes) for complete setup instructions.

## Getting started

### Prerequisites

* [Kubernetes installed](https://kubernetes.io/).

### Install `prefect-kubernetes`

The following command will install a version of `prefect-kubernetes` compatible with your installed version of `prefect`.
If you don't already have `prefect` installed, it will install the newest version of `prefect` as well.

```bash  theme={null}
pip install "prefect[kubernetes]"
```

Upgrade to the latest versions of `prefect` and `prefect-kubernetes`:

```bash  theme={null}
pip install -U "prefect[kubernetes]"
```

### Register newly installed block types

Register the block types in the `prefect-kubernetes` module to make them available for use.

```bash  theme={null}
prefect block register -m prefect_kubernetes
```

## Examples

### Use `with_options` to customize options on an existing task or flow

```python  theme={null}
from prefect_kubernetes.flows import run_namespaced_job

customized_run_namespaced_job = run_namespaced_job.with_options(
    name="My flow running a Kubernetes Job",
    retries=2,
    retry_delay_seconds=10,
) # this is now a new flow object that can be called
```

### Specify and run a Kubernetes Job from a YAML file

```python  theme={null}
from prefect import flow, get_run_logger
from prefect_kubernetes.credentials import KubernetesCredentials
from prefect_kubernetes.flows import run_namespaced_job # this is a flow
from prefect_kubernetes.jobs import KubernetesJob

k8s_creds = KubernetesCredentials.load("k8s-creds")

job = KubernetesJob.from_yaml_file( # or create in the UI with a dict manifest
    credentials=k8s_creds,
    manifest_path="path/to/job.yaml",
)

job.save("my-k8s-job", overwrite=True)


@flow
def kubernetes_orchestrator():
    # run the flow and send logs to the parent flow run's logger
    logger = get_run_logger()
    run_namespaced_job(job, print_func=logger.info)


if __name__ == "__main__":
    kubernetes_orchestrator()
```

As with all Prefect flows and tasks, you can call the underlying function directly if you don't need Prefect features:

```python  theme={null}
run_namespaced_job.fn(job, print_func=print)
```

### Generate a resource-specific client from `KubernetesClusterConfig`

```python  theme={null}
# with minikube / docker desktop & a valid ~/.kube/config this should ~just work~
from prefect_kubernetes.credentials import KubernetesCredentials, KubernetesClusterConfig

k8s_config = KubernetesClusterConfig.from_file('~/.kube/config')

k8s_credentials = KubernetesCredentials(cluster_config=k8s_config)

with k8s_credentials.get_client("core") as v1_core_client:
    for namespace in v1_core_client.list_namespace().items:
        print(namespace.metadata.name)
```

### List jobs in a namespace

```python  theme={null}
from prefect import flow
from prefect_kubernetes.credentials import KubernetesCredentials
from prefect_kubernetes.jobs import list_namespaced_job


@flow
def kubernetes_orchestrator():
    v1_job_list = list_namespaced_job(
        kubernetes_credentials=KubernetesCredentials.load("k8s-creds"),
        namespace="my-namespace",
    )
```

For assistance using Kubernetes, consult the [Kubernetes documentation](https://kubernetes.io/).

Refer to the `prefect-kubernetes` [SDK documentation](/integrations/prefect-kubernetes/api-ref/prefect_kubernetes-credentials) to explore all the capabilities of the `prefect-kubernetes` library.


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