Using Genie with Docker
Genie comes with extended support for containerizing apps using Docker. The functionality is provided by the official
In order to use the Docker integration features, first we need to add the
GenieDeployDocker plugin for
pkg> add GenieDeployDocker
Generating the Genie-optimised
You can bootstrap the Docker setup by invoking the
GenieDeployDocker.dockerfile() function. This will generate a custom
Dockerfile optimized for Genie web apps containerization. The file will be generated in the current work dir (or where instructed by the optional argument
path – see the help for the
Once generated, you can edit it and customize it as needed - Genie will not overwrite the file, thus preserving any changes (unless you call the
dockerfile function again, passing the
The behavior of
dockerfile() can be controlled by passing any of the multiple optional arguments supported.
Building the Docker container
Once we have our
Dockerfile ready, we can invoke
GenieDeployDocker.build() to set up the Docker container. You can pass any of the supported optional arguments to configure settings such as the container's name (by default
"genie"), the path (defaults to current work dir), and others (see the output of
help?> GenieDeployDocker.dockerfile for all the available options).
Running the Genie app within the Docker container
When the image is ready, we can run it with
GenieDeployDocker.run(). We can configure any of the optional arguments in order to control how the app is run. Check the inline help for the function for more details.
First let's create a Genie app:
julia> using Genie julia> Genie.Generator.newapp("DockerTest") [ Info: Done! New app created at /your/app/path/DockerTest # output truncated
When it's ready, let's add the
julia> using GenieDeployDocker julia> GenieDeployDocker.dockerfile() Docker file successfully written at /your/app/path/DockerTest/Dockerfile
Now, to build our container:
julia> GenieDeployDocker.build() # output truncated Successfully tagged genie:latest Docker container successfully built
And finally, we can now run our app within the Docker container:
julia> GenieDeployDocker.run() Starting docker container with `docker run -it --rm -p 80:8000 --name genieapp genie bin/server` # output truncated
We should then see the familiar Genie loading screen, indicating the app's loading progress and notifying us once the app is running.
Our application starts inside the Docker container, binding port 8000 within the container (where the Genie app is running) to the port 80 of the host. So we are now able to access our app at
http://localhost. If you navigate to
http://localhost w ith your favorite browser you'll see Genie's welcome page. Notice that we don't access on port 8000 - this page is served from the Docker container on the default port 80.
Inspecting the containers
We can get a list of available container by using
GenieDeployDocker.list(). This will show only the currently running containers by default, but we can pass the
all=true argument to also include containers that are offline.
julia> GenieDeployDocker.list() CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES c87bfd8322cc genie "bin/server" 6 minutes ago Up 6 minutes 80/tcp, 0.0.0.0:80->8000/tcp genieapp Process(`docker ps`, ProcessExited(0))
Stopping running containers
The running containers can be stopped by using the
GenieDeployDocker.stop() function, passing the name of the container.
Using Docker during development
If we want to use Docker to serve the app during development, we need to mount our app from host (your computer) into the container – so that we can keep editing our files locally, but see the changes reflected in the Docker container. In order to do this we need to pass the
mountapp = true argument to
GenieDeployDocker.run(), like this:
julia> GenieDeployDocker.run(mountapp = true) Starting docker container with `docker run -it --rm -p 80:8000 --name genieapp -v /Users/adrian/DockerTest:/home/genie/app genie bin/server`
When the app finishes starting, we can edit the files on the host using our favorite IDE, and see the changes reflected in the Docker container.
Creating an optimized Genie sysimage with
If we are using Docker containers to deploy Genie apps in production, you can greatly improve the performance of the app by preparing a precompiled sysimage for Julia. We can include this workflow as part of the Docker
build step as follows.
We'll start by making a few changes to our
Dockerfile, as follows:
1/ Under the line
WORKDIR /home/genie/app add
# C compiler for PackageCompiler RUN apt-get update && apt-get install -y g++
2/ Under the line starting with
RUN julia -e add
# Compile app RUN julia --project compiled/make.jl
You may also want to replace the line saying
ENV GENIE_ENV "dev"
ENV GENIE_ENV "prod"
to configure the application to run in production (first test locally to make sure that everything is properly configured to run the app in production environment).
We also need to add
PackageCompiler as a dependency of our app:
pkg> add PackageCompiler
Add the needed files
Create a new folder to host our files:
Now create the following files:
julia> touch("compiled/make.jl") julia> touch("compiled/packages.jl")
Edit the files
Now to put the content into each of the files.
Here we simply put an array of package that our app uses and that we want to precompile, ex:
# packages.jl const PACKAGES = [ "Dates", "Genie", "Inflector", "Logging" ]
Now edit the
make.jl file as follows:
# make.jl using PackageCompiler include("packages.jl") PackageCompiler.create_sysimage( PACKAGES, sysimage_path = "compiled/sysimg.so", cpu_target = PackageCompiler.default_app_cpu_target() )
Using the precompiled image
The result of these changes is that
PackageCompiler will create a new Julia sysimage that will be stored inside the
compiled/sysimg.so file. The last step is to instruct our
bin/server script to use the image.
bin/server file and make it look like this:
julia --color=yes --depwarn=no --project=@. --sysimage=compiled/sysimg.so -q -i -- $(dirname $0)/../bootstrap.jl -s=true "$@"
With this change we're passing the additional
--sysimage flag, indicating our new Julia sys image.