If you’re deploying to a single Droplet, I’m fairly certain that adding Docker is going to be more pain than gain*. I do not recommend using Docker for that situation unless you want to do it just for the learning process. And even if the learning process is important, I would still recommend getting the OTP release (Distillery) process learned without Docker first. OTP releases are complex and error-prone enough as it is.
Some folks listed some benefits that Docker may provide you, but again I wouldn’t reach for Docker until it’s clear you need those benefits.
*One thing Docker might be overall beneficial for you is if you use it to build your OTP release locally. You have to build your OTP release on the same OS distribution and version (e.g. Ubuntu 16.04) that the production machine is running. Docker gives you the ability to build your release locally in that OS distribution environment without having to manage a virtual machine. You would use the Docker container to run
mix release and write the files of the release to your local file system. Then those files can be tarred up, uploaded to your production Droplet, and deployed.
I suspect what someone said to you about not being able to run mix commands was actually about OTP releases, not Docker. One feature of OTP releases is that the production machine doesn’t need to have Elixir (or Erlang) installed on it. The Erlang runtime is included in the release. When you use mix on your development machine, it’s a system utility that is associated with your system Elixir. On your production machine running an OTP release, Elixir and mix aren’t there. But, just because you’re doing an OTP release doesn’t mean you can’t install Elixir and mix on the production machine yourself. You can do that. Just watch out for diverging Elixir versions.
It wasn’t until the host of ElixirTalk was telling me about how Docker slows their app to perform more efficiently and it made me wonder what everyone else was doing. Before I was using Distillery with edeliver on a DO droplet.
What they were probably talking about is the situation where you have multiple Docker containers running on a single machine. You can constrain the containers’ resources so that one container doesn’t use more than its fair share of resources.