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Here's my thought on 💭 Creating k8s jobs with python
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.
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)
This post was a thought by Waylon Walker see all my thoughts at https://waylonwalker.com/thoughts