title: How to run Tensorboard and jupyter concurrently with docker?
body: <p>I'm starting to learn how to use TensorFlow to do machine learning.  And find out docker is pretty convenient to deploy TensorFlow to my machine.  However, the example that I could found did not work on my target setting.  Which is</p>
  
  <p>Under ubuntu16.04 os, using nvidia-docker to host jupyter and tensorboard service together(could be two container or one container with two service).   And files create from jupyter should be visible to host OS.</p>
  
  <ul>
  <li>Ubuntu 16.04</li>
  <li>Dokcer</li>
  <li>nvidia-docker
  
  <ul>
  <li>Jupyter</li>
  <li>Tensorboard</li>
  </ul></li>
  </ul>
  
  <p>Jupyter container</p>
  
  <pre><code>nvidia-docker run \
      --name jupyter \
      -d \
      -v $(pwd)/notebooks:/root/notebooks \
      -v $(pwd)/logs:/root/logs \
      -e "PASSWORD=*****" \
      -p 8888:8888 \
      tensorflow/tensorflow:latest-gpu 
  </code></pre>
  
  <p>Tensorboard container</p>
  
  <pre><code>nvidia-docker run \
      --name tensorboard \
      -d \
      -v $(pwd)/logs:/root/logs \
      -p 6006:6006 \
      tensorflow/tensorflow:latest-gpu \
      tensorboard --logdir /root/logs
  </code></pre>
  
  <p>I tried to mount logs folder to both container, and let Tensorboard access the result of jupyter.  But the mount seems did work.  When I create new file in jupyter container with notebooks folder, host folder $(pwd)/notebooks just appear nothing.</p>
  
  <p>I also followed the instructions in <a href="https://www.tyneway.co/2017/03/nvidia-docker-jupyter-notebook-and-tensorflow-gpu/" rel="noreferrer">Nvidia Docker, Jupyter Notebook and Tensorflow GPU</a></p>
  
  <pre><code>nvidia-docker run -d -e PASSWORD='winrar' -p 8888:8888 -p 6006:6006 gcr.io/tensorflow/tensorflow:latest-gpu-py3
  </code></pre>
  
  <p>Only Jupyter worked, tensorboard could not reach from port 6006.</p>