Docker pt PT

Docker

Starting with version 3.0.3.2, ASF is now also available as docker container. Our docker packages are currently available on ghcr.io as well as Docker Hub.

It's important to note that running ASF in Docker container is considered advanced setup, which is not needed for vast majority of users, and typically gives no advantages over container-less setup. If you're considering Docker as a solution for running ASF as a service, then you should consider reading management section instead and set up a proper systemd service which will be almost always a better idea than running ASF in a Docker container.

While running ASF in docker container typically has no advantages for casual users (and causing several new problems on top of it), there are still valid use cases for it in very complex setups, for example in regards to advanced networking setup or security beyond standard sandboxing that ASF comes with in systemd service (which already ensures basic process isolation through very advanced security mechanics). For those handful amount of people, this section explains better ASF concepts in regards to its Docker compatibility.

Which tag is the best for me?

That depends on what you're looking for. For majority of users, latest tag should be the best one as it offers exactly what desktop ASF does, just in special Docker container as a service. People that are rebuilding their images quite often and would instead prefer full control with ASF version tied to given release are welcome to use released tag. If you instead want to use some specific frozen ASF version that will never change without your clear intention, A.B.C.D releases are available for you as fixed ASF milestones you can always fall back to.

We generally discourage trying main builds, as those are here for us to mark current state of ASF project. Nothing guarantees that such state will work properly, but of course you're more than welcome to give them a try if you're interested in ASF development.

Architectures

ASF docker image is currently built on linux platform targetting 3 architectures - x64, arm and arm64. You can read more about them in compatibility section.

Since ASF version V5.0.2.2, our tags are using multi-platform manifest, which means that Docker installed on your machine will automatically select the proper image for your platform when pulling the image. If by any chance you'd like to pull a specific platform image which doesn't match the one you're currently running, you can do that through --platform switch in appropriate docker commands, such as docker run. See docker documentation on image manifest for more info.

Usage

For complete reference you should use official docker documentation, we'll cover only basic usage in this guide, you're more than welcome to dig deeper.

Hello ASF!

Firstly we should verify if our docker is even working correctly, this will serve as our ASF "hello world":

docker run -it --name asf --pull always --rm justarchi/archisteamfarm

docker run creates a new ASF docker container for you and runs it in the foreground (-it). --pull always ensures that up-to-date image will be pulled first, and --rm ensures that our container will be purged once stopped, since we're just testing if everything works fine for now.

If everything ended successfully, after pulling all layers and starting container, you should notice that ASF properly started and informed us that there are no defined bots, which is good - we verified that ASF in docker works properly. Hit CTRL+P then CTRL+Q in order to quit foreground docker container, then stop ASF container with docker stop asf.

If you take a closer look at the command then you'll notice that we didn't declare any tag, which automatically defaulted to latest one. If you want to use other tag than latest, for example released, then you should declare it explicitly:

docker run -it --name asf --pull always --rm justarchi/archisteamfarm:released

Using a volume

If you're using ASF in docker container then obviously you need to configure the program itself. You can do it in various different ways, but the recommended one would be to create ASF config directory on local machine, then mount it as a shared volume in ASF docker container.

For example, we'll assume that your ASF config folder is in /home/archi/ASF/config directory. This directory contains core ASF.json as well as bots that we want to run. Now all we need to do is simply attaching that directory as shared volume in our docker container, where ASF expects its config directory (/app/config).

docker run -it -v /home/archi/ASF/config:/app/config --name asf --pull always justarchi/archisteamfarm

And that's it, now your ASF docker container will use shared directory with your local machine in read-write mode, which is everything you need for configuring ASF. In similar way you can mount other volumes that you'd like to share with ASF, such as /app/logs or /app/plugins.

Of course, this is just one specific way to achieve what we want, nothing is stopping you from e.g. creating your own Dockerfile that will copy your config files into /app/config directory inside ASF docker container. We're only covering basic usage in this guide.

Volume permissions

ASF container by default is initialized with default root user, which allows it to handle the internal permissions stuff and then eventually switch to asf (UID 1000) user for the remaining part of the main process. While this should be satisfying for the vast majority of users, it does affect the shared volume as newly-generated files will be normally owned by asf user, which may not be desired situation if you'd like some other user for your shared volume.

Docker allows you to pass --user flag to docker run command which will define default user that ASF will run under. You can check your uid and gid for example with id command, then pass it to the rest of the command. For example, if your target user has uid and gid of 1001:

docker run -it -u 1001:1001 -v /home/archi/ASF/config:/app/config --name asf --pull always justarchi/archisteamfarm

Remember that by default /app directory used by ASF is still owned by asf. If you run ASF under custom user, then your ASF process won't have write access to its own files. This access is not mandatory for operation, but it is crucial e.g. for auto-updates feature. In order to fix this, it's enough to change ownership of all ASF files from default asf to your new custom user.

docker exec -u root asf chown -hR 1001:1001 /app

This has to be done only once after you created your container with docker run, and only if you decided to use custom user for ASF process. Also don't forget to change 1001:1001 argument in both commands above to the uid and gid you actually want to run ASF under.

Multiple instances synchronization

ASF includes support for multiple instances synchronization, as stated in compatibility section. When running ASF in docker container, you can optionally "opt-in" into the process, in case you're running multiple containers with ASF and you'd like for them to synchronize with each other.

By default, each ASF running inside a docker container is standalone, which means that no synchronization takes place. In order to enable synchronization between them, you must bind /tmp/ASF path in every ASF container that you want to synchronize, to one, shared path on your docker host, in read-write mode. This is achieved exactly the same as binding a volume which was described above, just with different paths:

mkdir -p /tmp/ASF-g1
docker run -v /tmp/ASF-g1:/tmp/ASF -v /home/archi/ASF/config:/app/config --name asf1 --pull always justarchi/archisteamfarm
docker run -v /tmp/ASF-g1:/tmp/ASF -v /home/john/ASF/config:/app/config --name asf2 --pull always justarchi/archisteamfarm
# And so on, all ASF containers are now synchronized with each other

We recommend to bind ASF's /tmp/ASF directory also to a temporary /tmp directory on your machine, but of course you're free to choose any other one that satisfies your usage. Each ASF container that is expected to be synchronized should have its /tmp/ASF directory shared with other containers that are taking part in the same synchronization process.

As you've probably guessed from example above, it's also possible to create two or more "synchronization groups", by binding different docker host paths into ASF's /tmp/ASF.

Mounting /tmp/ASF is completely optional and actually not recommended, unless you explicitly want to synchronize two or more ASF containers. We do not recommend mounting /tmp/ASF for single-container usage, as it brings absolutely no benefits if you expect to run just one ASF container, and it might actually cause issues that could otherwise be avoided.

Argumentos de linha de comando

ASF allows you to pass command-line arguments in docker container through environment variables. You should use specific environment variables for supported switches, and ASF_ARGS for the rest. This can be achieved with -e switch added to docker run, for example:

docker run -it -e "ASF_CRYPTKEY=MyPassword" -e "ASF_ARGS=--no-config-migrate" --name asf --pull always justarchi/archisteamfarm

This will properly pass your --cryptkey argument to ASF process being run inside docker container, as well as other args. Of course, if you're advanced user then you can also modify ENTRYPOINT or add CMD and pass your custom arguments yourself.

Unless you want to provide custom encryption key or other advanced options, usually you don't need to include any special environment variables, as our docker containers are already configured to run with a sane expected default options of --no-restart --process-required --system-required, so those flags do not need to be specified explicitly in ASF_ARGS.

IPC

Assuming you didn't change the default value for IPC global configuration property, it's already enabled. However, you must do two additional things for IPC to work in Docker container. Firstly, you must use IPCPassword or modify default KnownNetworks in custom IPC.config to allow you to connect from the outside without using one. Unless you really know what you're doing, just use IPCPassword. Secondly, you have to modify default listening address of localhost, as docker can't route outside traffic to loopback interface. An example of a setting that will listen on all interfaces would be http://*:1242. Of course, you can also use more restrictive bindings, such as local LAN or VPN network only, but it has to be a route accessible from the outside - localhost won't do, as the route is entirely within guest machine.

For doing the above you should use custom IPC config such as the one below:

{
    "Kestrel": {
        "Endpoints": {
            "HTTP": {
                "Url": "http://*:1242"
            }
        }
    }
}

Once we set up IPC on non-loopback interface, we need to tell docker to map ASF's 1242/tcp port either with -P or -p switch.

For example, this command would expose ASF IPC interface to host machine (only):

docker run -it -p 127.0.0.1:1242:1242 -p [::1]:1242:1242 --name asf --pull always justarchi/archisteamfarm

If you set everything properly, docker run command above will make IPC interface work from your host machine, on standard localhost:1242 route that is now properly redirected to your guest machine. It's also nice to note that we do not expose this route further, so connection can be done only within docker host, and therefore keeping it secure. Of course, you can expose the route further if you know what you're doing and ensure appropriate security measures.

Complete example

Combining whole knowledge above, an example of a complete setup would look like this:

docker run -p 127.0.0.1:1242:1242 -p [::1]:1242:1242 -v /home/archi/ASF/config:/app/config --name asf --pull always justarchi/archisteamfarm

This assumes that you'll use a single ASF container, with all ASF config files in /home/archi/ASF/config. You should modify the config path to the one that matches your machine. This setup is also ready for optional IPC usage if you've decided to include IPC.config in your config directory with a content like below:

{
    "Kestrel": {
        "Endpoints": {
            "HTTP": {
                "Url": "http://*:1242"
            }
        }
    }
}

Pro tips

When you already have your ASF docker container ready, you don't have to use docker run every time. You can easily stop/start ASF docker container with docker stop asf and docker start asf. Keep in mind that if you're not using latest tag then using up-to-date ASF will still require from you to docker stop, docker rm and docker run again. This is because you must rebuild your container from fresh ASF docker image every time you want to use ASF version included in that image. In latest tag, ASF has included capability to auto-update itself, so rebuilding the image is not necessary for using up-to-date ASF (but it's still a good idea to do it from time to time in order to use fresh .NET runtime dependencies and the underlying OS).

As hinted by above, ASF in tag other than latest won't automatically update itself, which means that you are in charge of using up-to-date justarchi/archisteamfarm repo. This has many advantages as typically the app should not touch its own code when being run, but we also understand convenience that comes from not having to worry about ASF version in your docker container. If you care about good practices and proper docker usage, released tag is what we'd suggest instead of latest, but if you can't be bothered with it and you just want to make ASF both work and auto-update itself, then latest will do.

You should typically run ASF in docker container with Headless: true global setting. This will clearly tell ASF that you're not here to provide missing details and it should not ask for those. Of course, for initial setup you should consider leaving that option at false so you can easily set up things, but in long-run you're typically not attached to ASF console, therefore it'd make sense to inform ASF about that and use input command if need arises. This way ASF won't have to wait infinitely for user input that will not happen (and waste resources while doing so). It will also allow ASF to run in non-interactive mode inside container, which is crucial e.g. in regards to forwarding signals, making it possible for ASF to gracefully close on docker stop asf request.