Editing Tutorials:container which trains MNIST using Tensorflow (section)

== Uploading the final container to the cluster registry ==

Once you are happy with your code, you can upload the container image to the cluster registry just as in the basic tutorial before. Replace the tag by whatever you have used in the docker-compose.yml.

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docker push ccu-k8s.inf.uni-konstanz.de:32250/<your.username>/tf_mnist:0.1
</syntaxhighlight>

You can now execute this image from '''any''' computer which has the nvidia docker infrastructure installed and is logged into our cluster registry, for example like this:

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docker run --runtime=nvidia -d ccu.uni-konstanz.de:5000/<your.username>/tf_mnist:0.1
</syntaxhighlight>

This should give you an idea of how powerful this framework is. In particular, the image can now be executed from any compute node in the cluster, and it is ready to be deployed using Kubernetes.