We recommend using Docker Desktop due to it's integration with Windows and Windows Subsystem for Linux. However, while Docker Desktop supports running both Linux and Windows containers, you can not run both simultaneously. To run Linux and Windows containers simultaneously, you would need to install and run a separate Docker instance in WSL. If you need to run simultaneous containers or just prefer to install a container engine directly in your Linux distribution, follow the Linux installation instructions for that container service, such as Install Docker Engine on Ubuntu or Install Podman for running Linux containers.
Docker is a tool used to create, deploy, and run applications using containers. Containers enable developers to package an app with all of the parts it needs (libraries, frameworks, dependencies, etc) and ship it all out as one package. Using a container ensures that the app will run the same regardless of any customized settings or previously installed libraries on the computer running it that could differ from the machine that was used to write and test the app's code. This permits developers to focus on writing code without worrying about the system that code will be run on.
Working with Containers while working on Windows
Continuous availability, using Docker containers with tools like Kubernetes, is another reason for the popularity of containers. This enables multiple versions of your app container to be created at different times. Rather than needing to take down an entire system for updates or maintenance, each container (and it's specific microservices) can be replaced on the fly. You can prepare a new container with all of your updates, set up the container for production, and just point to the new container once it's ready. You can also archive different versions of your app using containers and keep them running as a safety fallback if needed.
In WSL version 1, due to fundamental differences between Windows and Linux, the Docker Engine couldn't run directly inside WSL, so the Docker team developed an alternative solution using Hyper-V VMs and LinuxKit. However, since WSL 2 now runs on a Linux kernel with full system call capacity, Docker can fully run in WSL 2. This means that Linux containers can run natively without emulation, resulting in better performance and interoperability between your Windows and Linux tools.
With the WSL 2 backend supported in Docker Desktop for Windows, you can work in a Linux-based development environment and build Linux-based containers, while using Visual Studio Code for code editing and debugging, and running your container in the Microsoft Edge browser on Windows.
Deploy containers on-premises by using AKS on Azure Stack HCI, Azure Stack with the AKS Engine, or Azure Stack with OpenShift. You can also set up Kubernetes yourself on Windows Server (see Kubernetes on Windows), and we're working on support for running Windows containers on RedHat OpenShift Container Platform as well.
Containers help developers build and ship higher-quality apps, faster. With containers, developers can create a container image that deploys in seconds, identically across environments. Containers act as an easy mechanism to share code across teams and to bootstrap a development environment without impacting your host filesystem.
Containers are portable and versatile, can run apps written in any language, and they're compatible with any machine running Windows 10, version 1607 or later, or Windows Server 2016 or later. Developers can create and test a container locally on their laptop or desktop, and then deploy that same container image to their company's private cloud, public cloud, or service provider. The natural agility of containers supports modern app development patterns in large-scale, virtualized cloud environments. The most useful benefit to developers is perhaps the ability to isolate your environment so that your app always gets the version of libraries that you specify, avoiding conflicts with dependencies.
Docker provides the ability to package and run an application in a loosely isolatedenvironment called a container. The isolation and security allows you to run manycontainers simultaneously on a given host. Containers are lightweight and containeverything needed to run the application, so you do not need to rely on what iscurrently installed on the host. You can easily share containers while you work,and be sure that everyone you share with gets the same container that works in thesame way.
Docker uses a client-server architecture. The Docker client talks to theDocker daemon, which does the heavy lifting of building, running, anddistributing your Docker containers. The Docker client and daemon canrun on the same system, or you can connect a Docker client to a remote Dockerdaemon. The Docker client and daemon communicate using a REST API, over UNIXsockets or a network interface. Another Docker client is Docker Compose,that lets you work with applications consisting of a set of containers.
The Docker daemon (dockerd) listens for Docker API requests and manages Dockerobjects such as images, containers, networks, and volumes. A daemon can alsocommunicate with other daemons to manage Docker services.
When you begin to work with containers, you will notice many similarities between a container and a virtual machine; but, in fact, these are two quite different concepts. Containers are going to change the way that we do Windows-based development work in the coming year, and they already underpin much of the devops work of speeding the delivery process. Nicolas Prigent explains how to use the Windows Containers feature.
Robert Sheldon wrote a great article about Windows containers on Simple Talk: -talk.com/cloud/platform-as-a-service/windows-containers-and-docker/. We will not dig deep once again into the concept of containers, but I will explain in this series how to create, run, convert and manage your Windows Containers.
Please note that Hyper-V containers are only managed by Docker, while Hyper-V Virtual Machines are managed by traditional tools such as Hyper-V Manager. In practice, booting Hyper-V containers takes longer than Windows Server Containers but both are much faster than a VM with a full OS (even on Nano Server).
The Visual Studio Code Dev Containers extension lets you use a container as a full-featured development environment. It allows you to open any folder inside (or mounted into) a container and take advantage of Visual Studio Code's full feature set. A devcontainer.json file in your project tells VS Code how to access (or create) a development container with a well-defined tool and runtime stack. This container can be used to run an application or to separate tools, libraries, or runtimes needed for working with a codebase.
Dotfiles are files whose filename begins with a dot (.) and typically contain configuration information for various applications. Since development containers can cover a wide range of application types, it can be useful to store these files somewhere so that you can easily copy them into a container once it is up and running.
A common way to do this is to store these dotfiles in a GitHub repository and then use a utility to clone and apply them. The Dev Containers extension has built-in support for using these with your own containers. If you are new to the idea, take a look at the different dotfiles bootstrap repositories that exist.
In addition, while Alpine support is available, some extensions installed in the container may not work due to glibc dependencies in native code inside the extension. See the Remote Development with Linux article for details.
On Windows nodes, strict compatibility rules apply where the host OS version mustmatch the container base image OS version. Only Windows containers with a containeroperating system of Windows Server 2019 are fully supported.
What we just did was to deploy two containers running a barebone Ubuntu docker image. Now, if we go in the Portal, under menu "Containers", we must see two containers within the App. One named "container1" and other named "container2". Both contain two volume mounts:
Let's run some tests by connecting to the containers terminal just to verify everything is working as they're supposed to. By the time of this writing, connecting to the Console in the Azure Portal in a specific container in a multi-container setup doesn't work. For that, we can use the az-cli to connect to both:
To verify both connections are working, just type command "ls" and check if you get back the list of root folders in the containers. One of the folders should be named "volumes" in that list. You now have two terminal windows open and ready to execute the next steps.
Remember, in the Container File System the changes are only visible for the local container inside that Container App. The files must not be shared to other containers within the Container App. Let's verify that by creating a new file named "test.log" under /volumes/container/ under container1 terminal window:
In a Temporary Storage, the files are shared across all containers within the same replica. Remember that when a Container App is scaling up, a new replica with the same set of containers is created. That new replica will not share the same Temporary Storage as the other replicas. So be aware about scaling up scenarios. Let's create a file under Temporary Storage path in container1:
The VPN configuration. When VPN is enabled all local networking is disabled. So if I ping the IP of the container, its routed to the corp network via the VPN and cannot identify the IP. So this fails. The only way is to enable local networking, but corp will not do this.
Although the output said to run podman machine start, I chose to run this machine as root, so I ran podman machine set --rootful before I ran podman machine start. This allows containers to run privileged operations, such as binding common system ports. In my walkthrough, I demonstrated port 8080, which is also compatible with rootless. It's easy to switch back and forth between running the podman machine in rootless or rootful mode. 2ff7e9595c