macondo: making Docker-wrapped applications easier to run

December 30, 2020

I found this article and it reminded me of a tool I wrote a couple of months ago called macondo.

In this post, I will try to explain what it is, why I wrote it and some of the drawbacks I’ve found. I am not trying to justify its existence of it or even suggesting this is the right way of doing things. I haven’t decided whether I like it or not.


macondo is a microframework that lets you package your scripts/applications in a Docker container, and run them as if they were regular, native programs. It does so by:

  • Automating the mounting of local files into the container for scripts that need to interact with them (e.g. tools that work with files in the current directory, or that need to access ~/.aws/credentials, etc.)
  • Making sure that files written/modified from the container have the right user ownership (i.e. the user id of the files will be the same as that of the host and not of the container).
  • Easily distribute/share “macondo commands”.

The problem

Developing/distributing software tools (especially for internal/private usage) poses some challenges:

  • Runtimes: people write tools in different languages and runtimes. In the same company, some people use bash, some like Ruby, or Python, or Java, etc. It is a pain to correctly set up the environment for all of the different tools.

    The user experience also sucks: a Ruby tool not only needs the right runtime but also requires you to manually set up its dependencies (e.g. installing bundler then running bundle install).

    Again, this is not just for Ruby. Almost every language needs a very specific runtime version and config to run properly.

    Languages that compile to native binaries might be more self-contained, but they still need to be compiled for different architectures/OS.

    And most importantly, having so many tools/languages available is good. You can use the language that best suits the problem at hand, or the one where you are most proficient, etc.

  • Reproducibility: you can’t ensure that the environment of your users is the same one you used to develop/test the application. Maybe your script depends on jq being installed, or terraform or awscliv1 but not awscliv2.

Docker to the rescue, kind of

Docker is a tool that helps alleviate this to some extent. It lets you package and distribute applications in environments tailored to run them without issues. Everything the application depends on is already in the container and so it solves the two problems above, kind of.

One of the issues with Docker is that it has an awkward interface when it comes to run CLI programs that work with local files. You need to understand what files the container needs, where it needs them and you need to explicitly mount them, etc.

Let’s make this more clear with an example.


Say we have an imaginary tool that receives a random string as an argument and then downloads a random dog image from Dog API, converts it into black and white, and uploads it to AWS S3. For the sake of simplicity, it is a bash script:

#!/usr/bin/env bash


# download random dog
curl -s | \
    jq -r '.message' | \
    xargs wget -O tmp.jpg

# make it black and white
convert tmp.jpg -colorspace gray $1.jpg
rm tmp.jpg

# push it to s3
aws --profile some-profile s3 cp $1.jpg s3://some-bucket/dogs/$1.jpg

Pretty simple script. Let’s see its dependencies: bash, curl, jq, xargs, ImageMagick, awscli, and good credentials in ~/.aws/credentials.

Say we want to distribute this and we package it so people can run it without worrying about the dependencies:

FROM alpine

RUN apk add bash jq imagemagick curl py3-pip util-linux
RUN pip3 install awscli icdiff

RUN chmod a+x /

WORKDIR "/output-folder"


Now we try to run it:

$ docker run -it dog foodogo
The config profile (some-profile) could not be found

It failed because the aws depends on the ~/.aws/credentials file, but this is running from the container, not the host. So we try:

$ docker run -v ~/.aws/credentials:/root/.aws/credentials:ro dog foodogo
$ ls
$ # there no files :( 

The dog image was downloaded and pushed to S3, but we can’t see it because it was in the container that no longer exists. So we try:

$ docker run -v ~/.aws/credentials:/root/.aws/credentials:ro -v $PWD:/output-folder dog foodogo
$ ls -l
-rw-r--r-- 1 root     root  26692 Dec 30 12:39 foodogo.jpg

Notice how we had to know about the Dockerfile structure so we could mount the current directory into the right folder. Also notice that the image is now in our local system but it is owned by the root user. This is problematic. The application would need to know beforehand the right user/group ID and then change the ownership of the file.

You get the idea… not only it is cumbersome to run the container with the right parameters, but also it does not necessarily interact nicely with the local file system.

Enter macondo

Now, here’s how it would work using macondo. We add the following annotations to the script:

#!/usr/bin/env bash
# @from Dockerfile
# @vol PWD:/output-folder
# @vol ~/.aws:~/.aws:ro
set -euo pipefail
.... the rest is the same

We see here two @annotations that macondo will use to build the image @from the local Dockerfile, and that tells it what folders to mount and how (@vol).

With that, you can run:

$ macondo foobar
$ ls -l
-rw-r--r-- 1 cristian users 49035 Dec 30 12:51 foobar.jpg

Notice that you don’t need to worry about manually mounting any directory, and that the file has the right permissions.

There’s a dry-run flag that can help demistify how this works:

$ macondo -0 foobar
docker run -i --env HOST_USER_ID=1001 --env HOST_GROUP_ID=100
--volume /home/cristian/scratch/example-macondo:/output-folder
--volume /home/cristian/.aws:/home/cristian/.aws:ro foobar

This is how it works: macondo builds a base Docker image using the Dockerfile but then writes an extra wrapper Docker image (here called with an ephemeral user that has the same name of my user, and the same user and group ids. That’s how it is able to generate the file with the right ownership.

Available annotations

Most of the features are enabled by adding @annotations to the script.

  • @from: can be Dockerfile to use the Dockerfile in the same directory as the command being run/build. But it can also receive a one-liner like @from AlpinePackages jq httpie ..., which builds an Alpine Linux docker image with the provided packages installed. It also work with UbuntuPackages.
  • @vol: can explicitly mount directories or files. It has the same syntax than Docker’s --volume flag. It also accepts PWD which resolves to the current directory, and ~ that resolves to $HOME. (e.g. @vol ~/foo:/bar)
  • @needs_ssh can be true or false (defaults to false). This mounts the SSH socket file from the host so that tools that rely on the SSH daemon work (e.g. git clone).
  • @needs_tty runs the Docker image with the --tty flag
  • @align_with_host_user enabled by default, creates an ephemeral user that has the same name, user, and group ID as the user running macondo.
  • @enable_dynamic_volume_mounts infers when a command is using a file in the host, even if it’s not in the current directory, and mounts it into the container (e.g. macondo something ../../some-file would mount that file or directory into the container so it can be accessed).
  • @user overrides the user the container runs with.
  • @workdir specifies the working directory of the container
  • @group, @description, @name, @version are used to organize, build, and publish Docker images. macondo supports the concept of “repositories”, allowing to run commands for which the source code is not available locally. More on this later.

It’s worth noticing that other than the extra annotations, the script can still be run directly (in the example above ./

Also, this works for any kind of scripts (Python, Ruby, etc.) and any kind of application. For instance, this is the “macondo file” for a JVM application written in Ballerina:

# @from Dockerfile
# @version 0.1.0
# @description Takes a savepoint from the specified Flink job
# @group Flink

In this case, it is the responsibility of the Dockerfile to build/package the application in the right way.

Publishing commands

So far we have used macondo to run a local script. But that’s not its intended use. In my use case, I have a plethora of commands and CLI tools that I make available to coworkers.

The idea is that they only need to install macondo once and set up one or more repositories that allow them to run these commands. They do not need access to the source code or binaries of the applications because these live in a Docker registry.

macondo repositories are YAML manifests that contain information about the programs, their annotations, and their Docker image location. These can be created using the macondo build -y command:

$ mv # commands you want to publish need to have the .mcd extension
$ macondo build -y -p cristianc/dog . | tee repository.yaml
Built and published to cristianc/
  - name: dog
    group: ""
    .... etc.

The previous command builds our dog macondo command (which is in the current directory, hence the .), publishes the Docker image to DockerHub (in a real-world case this would be an ECR repository for instance), and writes a YAML repository file to repository.yaml.

This YAML file is what you will actually distribute. I usually keep it in Artifactory or a Gist, and hand it to my users (i.e. coworkers).

By the way, macondo build will traverse the provided directory looking for .mcd files to build, and it will publish them all. Here’s an example run of a real-world directory with commands:

macondo build ~/src/company-cmds/

To add a repository to macondo use the macondo repo command:

$ macondo repo add manifest.yaml # or http url

Another advantage of putting the manifest in a static HTTP endpoint is that you can override it with newer versions of your commands, or more commands, and all your users need to do to access this commands is run macondo repo update.

All commands in the added repository will be accessible as macondo subcommands. e.g. this shows all commands my current macondo repositories provide:

$ macondo
You forgot to provide a command...

Flink commands:

  flink-gen-tfm            Generates scaffolding terraform for a Flink job
  flink-savepoint          Takes a savepoint from the specified Flink job
  flink-deploy             Deploys a Flink job to any environment
  flink-jenkins            Generates Jenkins task for a Flink job
  build-flink              Builds Flink from source code
  flink-inspect            Scrapes information from a job running on the provided job manager's url(s)
  flink-list               Lists all jobs currently running on a particular Kubernetes cluster

Ververica commands:

  suspend-job              Generates Flink CI/CD terraform from a Ververica deployment
  ververica-gen-tfm        Generates Flink CI/CD terraform from a Ververica deployment

Data Team commands:

  get-ladot-device         Gets the latest state of a vehicle in the LADOT account

Personal commands:

  process-videos           Concats all the videos in the provided folder and pushes them to Youtube

The good and the bad parts

So far my experience with this approach has been pleasant. But of course I am biased. I’ve come to use it even for personal tools. These are the bits I like:

  • Can be used by anyone that has docker installed, regardless of whether they use Mac or Linux (haven’t tested this in Windows).
  • You can iterate on the tools locally, and publish them by updating the manifest. All your users need to do to access new commands or versions of them is run macondo update.
  • It makes the development of polyglot tools a breeze. As long as you can package it in Docker anyone can run it.

These are the things I dislike:

  • The “fake user id” part is a bit hacky. So far I support Ubuntu and Alpine Docker base images only, and even for those two I have to do it differently.
  • The Docker images might sometimes be too fat for what they package. At least the first time a user runs a macondo command it will take a while because the image has to be fetched and then it has to be wrapped to fake the user id.
  • It obscures the application. When you run a regular script and it does not work you can at least inspect it and figure out. When it is run through something like macondo, and wrapped in Docker, etc. it becomes harder to figure out when things do not go as planned.

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