A quick (but unsafe) solution:
Launch:
tensorboard --logdir=/training --host=0.0.0.0 --port=8080
on your AWS instance.
Make sure that both inbound and outbound rules on the AWS console (control center) are as unlimited as possible (allow all types, all ports, etc.). However, keep in mind that this solution is not recommended for environments requiring security (in our case, we did not consider the safety of NN training).
Trying to explain why this works: when the policy is set as described, AWS still seems to block incoming / outgoing connections on the standard tensor port 6006. This does not seem to apply to port 8080.
Longer (but safer) solution: See: https://blog.altoros.com/getting-started-with-a-cpu-enabled-tensorflow-instance-on-aws.html (provides explanations of the correct installation of ports on AWS )
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