Using Docker for Dev environments
I had put some thought into using Docker locally as part of development, but after a talk about maintaining boxen scripts (used to provision macs according to a common set of requirements for projects) it got me thinking about what you could really do with containers for development environments and flow.
My experience on different projects with development environments has been mostly bad over the years.
Commonly there's nothing to help with setup, developers just get some (sketchy) documentation about what applications and dependencies they need to run and change the solution. This leads to problems when working in teams, increasing time to get developers started and lots of "works on my machine" environmental differences. Because developers are running everything locally the environment they are building and testing on is nothing like the intended production environment (different dependencies/OS/Architecture etc.), so developers have no visiblity of problems that occur when their code is deployed. This causes the "throwing problems over the wall" gap between developers and operations.
Sometimes there's a standard development VM image, which is better than manual configuration but also introduces new problems. It's normally a beast, large in file size and poorly performing (to the point that developers work to avoid using it). It's also hard to maintain, as no one wants to re-install a multi-gigabyte image, so it tends to become a base image needing manual corrections for updates rather than plug and play environment. It also shares a lot of the same problems with differences from production, as it's not practical to use virtual machines replicating the production environment/architecture running on a normal laptop/desktop.
Containers offer new possibilities for development environments. When running directly on the host (not inside a virtual machine like boot2docker) it offers near native performance. Containers are small in size, so can be created/destroyed quickly and are very fast to start, meaning you can rebuild your environment per change. Container image definitions and scripts for rebuilding/starting them can be stored in source control, using the same definitions in development, build, test and production environments, reducing the differences between them. Because of the size/performance benefits we can be more ambitious on how far we go in simulating production conditions, introducing load balancing and networking concerns early in development, allowing developers to see these early rather than leaving it all to operations staff.
Below is a diagram showing an example of this setup:
Optionally, containers aren't just limited to headless processes, you can run GUI applications too like IDEs. This allows pre-configured development tools to be tailored specifically for the project, to quickly allow new developers to start with the same toolset as the rest of the team. Isolating the entire development stack inside containers means developers don't have to alter their own machine setup to work on a project, reducing startup time and making it easier to switch between projects without rebuilding their machine.