We are very excited to announce a new Azure driver for Docker Machine. Docker Machine is a tool that lets you create virtual machines with Docker on your laptop or on cloud providers and manage them. It makes developing with containers locally on your development machine easy and lets you orchestrate your container hosts on the cloud.
Microsoft Azure has been contributing to Docker Machine since the beginning of the project. In October 2014, we released the first version of Azure driver for Docker Machine that used Azure Service Management APIs to create virtual machines on Azure.
Today, we are updating Docker Machine Azure Driver to use the Azure Resource Manager APIs. With this release, we are adding a number of features, giving finer control to the users and making it a lot easier to use.
Please check out the following demo of the new Docker Machine that creates a Linux VM on Azure running the Docker Engine.
The updated version of Docker Machine Azure driver is going to be released with docker-machine v0.7.0. You can get it as a binary from GitHub or by installing Docker Toolbox.
Please note, the new Azure driver for Docker Machine is not backwards compatible: The existing machines created with the docker-machine versions v0.6.0 or older cannot be managed using the new Azure driver.
The reason for incompatibility is the incompatibility between the old Azure Service Management APIs and the new Azure Resource Manager APIs used in the old driver vs. the new driver. This is making it impossible to manage older machines with the new driver or migrate them. We suggest removing machines created with the old driver and recreating them with the new driver for a smooth transition. If you run into this problem, please downgrade your docker-machine version to v0.6.0 or older.
Try it out
You can try the new Docker Machine Azure driver by downloading Docker Machine v0.7.0 (or newer) from GitHub or by installing Docker Toolbox.
Please refer to Docker Machine documentation and Azure driver reference. Please let us know if you encounter any issues by opening issues at docker/machine repo on GitHub.