Docker-compose files can become quite complex and in some cases you would like to document not just the docker-compose.yml content, but also visualize how the different docker-compose service communicate. Furthermore, it can be quite interesting to reverse-engineer docker files to get a better understanding, what they are build of.

There are different ways to do so and I want to dig into some of the most popular ones.


Starting with dfimage, a reverse-engineering project for Docker files, that simplifies that task a lot.

You can simply use the available dockerhub image, if you like, or of course build the project yourself.

To run the image against a local (already pulled) docker image, simply execute:

docker images # to pick your image id

or pull an image

docker pull grafana/grafana #as an example

docker run -v /var/run/docker.sock:/var/run/docker.sock laniksj/dfimage imageID

docker run -v /var/run/docker.sock:/var/run/docker.sock laniksj/dfimage 808a15f85914

The project needs access to the docker.sock to access the image details, therefore run it with -v /var/run/docker.sock …

The output for the Grafana image looks like that and can give you a pretty good idea, how the image was build:

FROM grafana/grafana:latest
ADD file:fe64057fbb83dccb960efabbf1cd8777920ef279a7fa8dbca0a8801c651bdf7c in /
CMD ["/bin/sh"]
ENV PATH=/usr/share/grafana/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin GF_PATHS_CONFIG=/etc/grafana/grafana.ini GF_PATHS_DATA=/var/lib/grafana GF_PATHS_HOME=/usr/share/grafana GF_PATHS_LOGS=/var/log/grafana GF_PATHS_PLUGINS=/var/lib/grafana/plugins GF_PATHS_PROVISIONING=/etc/grafana/provisioning
WORKDIR /usr/share/grafana
RUN |2 GF_GID=472 GF_UID=472 /bin/sh -c apk add –no-cache ca-certificates bash
&& apk add –no-cache –upgrade –repository= openssl musl-utils
RUN |2 GF_GID=472 GF_UID=472 /bin/sh -c if [ `arch` = "x86_64" ]; then apk add –no-cache –virtual phantomjs-utils curl
&& cd /tmp
&& curl -Ls | tar xz
&& cp -R lib lib64 /
&& cp -R usr/lib/x86_64-linux-gnu /usr/lib
&& cp -R usr/share/fonts /usr/share
&& cp -R etc/fonts /etc
&& rm -rf /tmp/*
&& apk del –no-cache phantomjs-utils; fi
COPY dir:44ba505a8722a860c8980bd5fc72dc9df74b7364a65579eaf9df86a41f1492e4 in /usr/share/grafana
RUN |2 GF_GID=472 GF_UID=472 /bin/sh -c mkdir -p "$GF_PATHS_HOME/.aws"
&& addgroup -S -g $GF_GID grafana
&& adduser -S -u $GF_UID -G grafana grafana
&& cp "$GF_PATHS_HOME/conf/sample.ini" "$GF_PATHS_CONFIG"
&& cp "$GF_PATHS_HOME/conf/ldap.toml" /etc/grafana/ldap.toml
COPY file:3e1dfb34fa6281634e9860cf1caea6384f6978cb513eb33b07f04752b4879694 in /
USER grafana

dive docker image

The project can be found here:


dive is a tool to explore every single layer of a docker image. It can not just help to audit a docker image, but also to find ways to shrink your image size.

As always you can either build the dive command, download a release or use a docker container. I use the debian release v.0.8.1 in that example:

sudo dpkg -i dive_0.8.1_linux_amd64.deb

check the Grafana image

dive 808a15f85914
Fetching image… (this can take a while with large images)
Parsing image…
Analyzing image…
Building cache…

dive usage demo Dockerfile

The project demo video

Our Grafana image looks more like that 

dive grafana image

Another nice dive feature is the integration into a CI build process, by setting the CI variable to true

CI=true dive

The release downloads can be found here:

The dive project can be found here:


The last project I want to cover is the visualization of a docker-compose file. That’s very convenient, when you want to visualize the communication between ports or different services inside your docker-compose file. It’s using the graphviz project to create a image file. Just make sure, you’re running the following command within the same directory as the docker-compose.yml file and make sure you have write permissions. 

After running the command you’ll find the docker-compose.png file within that directory as well.

docker run –rm -it –name dcv -v $(pwd):/input pmsipilot/docker-compose-viz render -m image docker-compose.yml

This example is a simple prest/postgres project based on the following docker-compose.yml file:

version: "3"
image: prest/prest

  • "postgres:postgres"
  • PREST_DEBUG=true # remove comment for enable DEBUG mode (disable JWT)
  • PREST_PG_HOST=postgres
  • PREST_PG_USER=prest

    – PREST_PG_PASS=prest

  • PREST_PG_PORT=5432
  • PREST_JWT_DEFAULT=false # remove if need jwt
  • postgres
  • "13000:3000"
    image: postgres:latest
  • "./data:/var/lib/postgresql/data"
  • POSTGRES_DB=prest


  • "15432:5432"

docker-compose prest visualize

or dgraph:

version: "3.2"
image: dgraph/dgraph:latest

  • type: volume
    source: dgraph
    target: /dgraph
    nocopy: true
  • 5080:5080
  • 6080:6080
    restart: on-failure
    command: dgraph zero –my=zero:5080
    image: dgraph/dgraph:latest
  • type: volume
    source: dgraph
    target: /dgraph
    nocopy: true
  • 18080:8080
  • 19080:9080
    restart: on-failure
    command: dgraph alpha –my=server:7080 –lru_mb=2048 –zero=zero:5080
    image: dgraph/dgraph:latest
  • type: volume
    source: dgraph
    target: /dgraph
    nocopy: true
  • 8000:8000
    command: dgraph-ratelvolumes:

dgraph viz

Depending on the amount and complexity of the services, you can get some decent sized images generated – so make sure to have a big screen. 

The docker-compose viz project can be found here:

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immudb runs embedded on the IoT device itself and is consistently audited by external probes. The data transfer to audit is minimal and works even with minimum bandwidth and unreliable connections.

Whenever the IoT devices are connected to a high bandwidth, the data transfer happens to a data center (large immudb deployment) and the source and destination date integrity is fully verified.

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A very high Performance is required as the system should not slow down any build process.
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Next to a possibility of integrity validation, data needs to be retrievable by pipeline job id or digital asset checksum.


As part of the CI/CD audit functionality, data is stored within immudb using the Key/Value functionality. Key is either the CI/CD job id (i. e. Jenkins or GitLab) or the checksum of the resulting build or container image.

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