.github/workflows | ||
.dockerignore | ||
.editorconfig | ||
.gitignore | ||
docker-compose.yml | ||
docker-network-graph.py | ||
Dockerfile | ||
example.png | ||
example.svg | ||
LICENSE | ||
Pipfile | ||
Pipfile.lock | ||
README.md |
Docker Network Graph
Visualize the relationship between Docker networks and containers as a neat graphviz graph.
This repository fork e-dant/docker-network-graph Changes:
- Improved design
- Added the ability to generate url
- Added display of connections with the host
- Visualization of ports
- Github package
Example
Usage
usage: docker-network-graph.py [-h] [-v] [-o OUT] [-u]
Visualize docker networks.
optional arguments:
-h, --help Show this help message and exit
-v, --verbose Verbose output
-o OUT, --out OUT Write output to file [not supported by container]
-u, --url Generate link for GraphvizOnline
Running inside docker
If you want to generate a graph for a remote system you can also easily run this script inside a pre-built docker container:
docker run --rm -v /var/run/docker.sock:/var/run/docker.sock ghcr.io/muratovas/docker-network-graph:latest -u
For more advanced use cases you can append arguments to the docker run
command as if you were running it in a local shell.
Running local
In most cases what you want to run are the following couple commands:
git clone https://github.com/muratovas/docker-network-graph.git
cd docker-network-graph
pipenv install
pipenv run python docker-network-graph.py -o output.svg
This will generate an .svg file containing the graph.
This will just generate and output the graph in the [DOT Language][dot].
You can then paste that code into [GraphvizOnline][gvonline]
to render it. The recommended rendering engine is fdp
.
Alternatively, if you prefer to render locally, you can run
fdp -Tpng -o out.png
on a system with graphviz installed,
paste the previous output there, press enter and finally CTRL+C to
generate the file.
Development
If you'd like to contribute to this project, there is a sample docker-compose file
using dummy containers in test
.
You can deploy it using
docker-compose -f docker-compose.yml up -d