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→Logging to Tensorboard from within your container
[https://itnext.io/how-to-use-tensorboard-5d82f8654496 this here].
== Viewing the Tensorboard of the job ==
First, find out the compute node your pod was allocated to.
<syntaxhighlight lang="python">
> kubectl get pods | grep your-username
NAME READY STATUS RESTARTS AGE
your-username-tf-mnist-tb-pvc-mqt9m 1/1 Running 0 3m4s
> kubectl describe pod your-username-tf-mnist-tb-pvc-mqt9m | grep Node
Node: glasya/134.34.226.30
</syntaxhighlight>
Your pod is running on Glasya, IP 134.34.226.30. You can now point your browser to 134.34.226.30:6116 to access the Tensorboard instance for the node. Note that it lists the logs for all currently mounted PVs. To find out which is your mount point, you need to check which directory your PVC was bound to:
<syntaxhighlight lang="python">
> kubectl get pvc | grep your-username
your-username-tf-mnist-tb-pvc Bound local-pv-d07aa16c 25Gi RWO local-tensorboard 19m
> kubectl describe pv local-pv-d07aa16c | grep Path
Path: /mnt/tensorboard/glasya-pv-tb-25gb-2
</syntaxhighlight>
This means that your logs will be the ones prefixed by "glasya-pv-tb-25gb-2" in the Tensorboard instance.
[[Category:Tutorials]]
