ML102 k8s example

Running it

The pod will de deployed to the kai-test namespace and will be named ml102-test. You may need to change the name of the pod if there is already one with the same name running (kubectl -n kai-test get pods).

1. Make sure kubectl is configured
2. Edit ml102-example-pod.yaml if required
3. Launch the pod with:

   kubectl apply -f ml102-example-pod.yaml
   

4. Check status of the pod (changing the name of the pod if required):

   kubectl -n kai-test describe pod ml102-test
   

5. Once the pod is running, setup port forwarding (changing name of the pod if required)

   kubectl -n kai-test port-forward pod/ml102-test 8888:8888
   

6. Connect to http://localhost:8888
   • notebooks should be available in the notebooks directory
   • open a Jupyter terminal and run nvidia-smi to check the GPU state

Building the docker image

• The docker image should build automatically when you push changes
• Based on an older GPU enabled tensorflow image (the notebooks haven't been updated in a while and throw lots of warnings with newer tensorflow)