How to run Tensorboard and jupyter concurrently with docker?

I was facing the same problem today.

Short answer: I'm going to assume you are using the same container for both Jupyter Notebook and tensorboard. So, as you wrote, you can deploy the container with:

nvidia-docker run -d --name tensor -e PASSWORD='winrar'\
                  -p 8888:8888 -p 6006:6006 gcr.io/tensorflow/tensorflow:latest-gpu-py3

Now you can access both 8888 and 6006 ports but first you need to initialize tensorboard:

docker exec -it tensor bash
tensorboard --logdir /root/logs

About the other option: running jupyter and tensorboard in different containers. If you have problems mounting same directories in different containers (in the past there was a bug about that), since Docker 1.9 you can create independent volumes unlinked to particular containers. This may be a solution.

1. Create two volumes to store logs and notebooks.
2. Deploy both images with these volumes.

docker volume create --name notebooks
docker volume create --name logs 

nvidia-docker run \
--name jupyter \
-d \
-v notebooks:/root/notebooks \
-v logs:/root/logs \
-e "PASSWORD=*****" \
-p 8888:8888 \
tensorflow/tensorflow:latest-gpu

 nvidia-docker run \
 --name tensorboard \
 -d \
 -v logs:/root/logs \
 -p 6006:6006 \
 tensorflow/tensorflow:latest-gpu \
 tensorboard --logdir /root/logs