How to communicate between WIN10 system and Docker internal container IP

1. After installing the Windows version of Docker, we start the Docker Quickstart Terminal and we will get an IP address. Mine is:

192.168.99.100

2. Start a mysql image and get the IP of this image:

At the beginning, the network is not accessible from the local machine directly to 172.17.0.2, but our local machine can reach 192.168.99.100, and 172.17.0.2 to 192.168.99.100 is also accessible. We can configure a route from the local machine to 172.17.0.2 via 192.168.99.100:

route add -p 172.17.0.0 mask 255.255.0.0 192.168.99.100

Check the route and you will see that there is a route to the 172.17.0.0 network segment.

At this time, we can ping 172.17.0.2 from our local machine. Then we use navicat to connect to the mysql container in Docker:

Additional knowledge: Bugs that occur during the use of docker

This record is about some bugs that occurred when using Docker and how I solved them. The bugs encountered when using Docker will be supplemented later.

Bug 1, verify whether nvidia-docker is installed successfully (enter the command sudo nvidia-docker run --rm nvidia/cuda nvidia-smi, the following error is generated)

lab712@lab712:~$ sudo nvidia-docker run --rm nvidia/cuda nvidia-smi

docker: Error response from daemon: OCI runtime create failed: container_linux.go:344: starting container process caused "process_linux.go:424: container init caused \"process_linux.go:407: running prestart hook 1 caused \\\"error running hook: exit status 1, stdout: , stderr: exec command: [/usr/bin/nvidia-container-cli --load-kmods configure --ldconfig=@/sbin/ldconfig.real --device=all --compute --utility --require=cuda>=10.0 brand=tesla,driver>=384,driver<385 --pid=4760 /var/lib/docker/overlay2/2b42e419162d46fad61c0a70cbb7b16c79a8878f2dab1af682dbff4813b57316/merged]\\\\nnvidia-container-cli: requirement error: unsatisfied condition: brand = tesla\\\\n\\\"\"": unknown.

Check the image files installed on your computer and find that when installing nvidia-docker, three nvidia/cuda with different tags (TAGs) were pulled, as shown in Figure 1 below. The graphics card driver is installed. Since I did not specify the nvidia/cuda tag (TAG) when using the command, the tag latest will be directly called by default.

After re-specifying the tag (TAG), enter the command: nvidia-docker run --rm nvidia/cuda:9.0-base nvidia-smi , and it will be successful. The results are shown in Figure 2.

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