Perhaps because Docker has great stories for deployment. Many of the complexities of deployment are handled for you (writing a systemd unit, managing rollback, etc).
The complexity of Docker is not that big for a Go deployment though, especially if you have all the other bits for orchestrating your Docker containers (for the rest of your stack) already in place. You mostly just copy the binary into a slim image and you are done.
You don't need docker for that, just 'tar czf my-layer.tar.gz my-dir'. If you want a manifest file, you can get the digest using `sha256sum my-layer.tar.gz`.
Docker does this quite well, and solves a bunch of other problems you're likely to have regardless. One really simple example is "how do you copy it to the server?" Do you have ssh keys for your server on development machines? How do you handle the "Oh I'll just remote in and fix this one X"?
It's also _crazily_ easy to get started with, and handle middling amounts of scale. If you're on AWS, Elastic Beanstalk is plug and play. If you're not, DigitalOcean App platform will host it for you, with automated deployments from git for $5/month with basically no configuration needed from you.
Publishing your docker image to some open or private store still needs to happen. Then the host needs to be updated. This is not really that much simpler than "scp your binaries to the server". And has many more moving parts that can fail.
Now, there are better ways to distribute go projects than scp, for example heroku style or by just abusing its builtin git support.
Of course, if you're doing somethign in Python/Ruby/Node.js then it's useful because these language do not provide a reliable method to compile source code into an independent program/application.
But that does not make it "awesome" or anything. It's just a band-aid. It's an extra layer to hide fundamental design problems.
With Go, the root problem is solved: the language has a compiler that reliably produces statically linked binary executable programs.
This is the very first time I ever heard such nonsense. In all companies I've been, Docker is a renowned problem solver, not only for production deplyments but also for local testing environments and deployments.
It even shines as a stand-alone barebones clustering solution with Docker swarm mode.
I find it quite amusing that projects that try to position themselves as Docker alternatives end up basing their presentation on how their project can be used just like Docker, down to Docker's choice of command line interface.