I was looking to add running kubernetes jobs to a python cli I am creating, and I found this solution, mostly thanks to `ollama run mistral:7b-instruct-q4_K_M ` and my loose understanding of what the yaml syntax is supposed to look like for a kubernetes job. This will let me create a job in the cluster, choose the image that runs, the command that is called, and how long until the job expires and is cleaned up. While the job still exists I can go in and look at the logs, but once its ttl has expired they are gone.
``` python
from kubernetes import client, config
# Load the default kubeconfig
config.load_kube_config()
# Define the API client for batch jobs
api_instance = client.BatchV1Api()
# Create a new job object
job = client.V1Job(
api_version="batch/v1",
kind="Job",
metadata=client.V1ObjectMeta(name="myjob"),
spec=client.V1JobSpec(
ttl_seconds_after_finished=100,
template=client.V1PodTemplateSpec(
metadata=client.V1ObjectMeta(labels={"app": "myjob"}),
spec=client.V1PodSpec(
containers=[
client.V1Container(
name="myjobcontainer",
image="busybox",
command=["ls", "/"],
),
],
restart_policy="Never",
),
),
backoff_limit=1,
),
)
# Call the Kubernetes API to create the job
api_instance.create_namespaced_job(namespace="default", body=job)
```
!!! note
This post is a thought. It's a short note that I make
about someone else's content online #thoughts