Container Layer Analyzer

Have you ever wondered what exactly is eating up your precious space in each
layer of your container images? Would you like to have a nice visualization of
the file system similarly to what
Baobab provides?

In that case this is the tool you are looking for: it provides a simple web UI
that shows you the size of your file system inside any publicly accessible



Run it

To run this on your local machine, you’ll need the following tools:

  • podman configured to work in rootless mode
  • node.js and yarn
  • golang
  • the prerequisites to build (see

When you have these tools set up, clone the repository and run:

$ git clone
$ cd container-layer-sizes.git
$ yarn install
$ yarn run build
$ ./container-layer-sizes

The web UI is then accessible on localhost:5050.

What is missing?

  • proper documentation
  • better tests
  • actual error handling and better feedback via the UI
  • performance improvements
  • support local images

How does this work?

The go binary is a simple web server that serves the frontend code and analyzes
the container sizes. The size analysis works as follows:

  1. The requested container image is pulled from a registry into the local
    container storage (i.e. the equivalent of podman pull). The image is then
    extracted into a temporary directory. This gives us each layer as an archive.

  2. Each layer is analyzed using the
    archiver.Walk() function
    and the whole directory tree is saved in a Dir struct (see
    dir.go). The resulting structures are converted to json and
    sent to the frontend.

  3. The frontend code receives the data from the backend and has to perform some
    conversion so that the data can be visualized as a sunburst chart via
    Currently we also cut of paths that are deeper than five subdirectories, as
    otherwise the frontend page becomes very sluggish.


  1. Should I run this in production?

Absolutely not! There is no logging, no cleanup and no security audit has been
perform. Please only run this for testing on your local machine for now.


View Github