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→Checking in on the container
</syntaxhighlight>
== Checking in on the container job ==
We first check if our container is running.
root@tf-mnist-xxxxx:/workspace#
</syntaxhighlight>
== Shutting down the job early ==
If while inspecting the job you notice that it does not run correctly, you can shut it down prematurely with
<syntaxhighlight lang="bash">
> kubectl delete -f job_script.yaml
</syntaxhighlight>
Note that this also deletes all data your container might have written to its filesystem layer. If you want to save your trained models, you have to mount persistent volumes from the Kubernetes cluster into the container. This is covered in the [[Tutorials:Persistent volumes|persistent volume tutorial]].
