Docker originally used LinuX Containers (LXC), but later switched to runC (formerly known as libcontainer), which runs in the same operating system as its host. This allows it to share a lot of the host operating system resources. Also, it uses a layered filesystem (AuFS) and manages networking.
AuFS is a layered file system, so you can have a read only part and a write part which are merged together. One could have the common parts of the operating system as read only (and shared amongst all of your containers) and then give each container its own mount for writing.
So, let’s say you have a 1 GB container image; if you wanted to use a full VM, you would need to have 1 GB x number of VMs you want. With Docker and AuFS you can share the bulk of the 1 GB between all the containers and if you have 1000 containers you still might only have a little over 1 GB of space for the containers OS (assuming they are all running the same OS image).
A full virtualized system gets its own set of resources allocated to it, and does minimal sharing. You get more isolation, but it is much heavier (requires more resources). With Docker you get less isolation, but the containers are lightweight (require fewer resources). So you could easily run thousands of containers on a host, and it won’t even blink. Try doing that with Xen, and unless you have a really big host, I don’t think it is possible.
A full virtualized system usually takes minutes to start, whereas Docker/LXC/runC containers take seconds, and often even less than a second.
There are pros and cons for each type of virtualized system. If you want full isolation with guaranteed resources, a full VM is the way to go. If you just want to isolate processes from each other and want to run a ton of them on a reasonably sized host, then Docker/LXC/runC seems to be the way to go.
Why is deploying software to a docker image (if that’s the right term) easier than simply deploying to a consistent production environment?
Deploying a consistent production environment is easier said than done. Even if you use tools like Chef and Puppet, there are always OS updates and other things that change between hosts and environments.
Docker gives you the ability to snapshot the OS into a shared image, and makes it easy to deploy on other Docker hosts. Locally, dev, qa, prod, etc.: all the same image. Sure you can do this with other tools, but not nearly as easily or fast.
This is great for testing; let’s say you have thousands of tests that need to connect to a database, and each test needs a pristine copy of the database and will make changes to the data. The classic approach to this is to reset the database after every test either with custom code or with tools like Flyway – this can be very time-consuming and means that tests must be run serially.
However, with Docker you could create an image of your database and run up one instance per test, and then run all the tests in parallel since you know they will all be running against the same snapshot of the database. Since the tests are running in parallel and in Docker containers they could run all on the same box at the same time and should finish much faster. Try doing that with a full VM.
Interesting! I suppose I’m still confused by the notion of “snapshot[ting] the OS”. How does one do that without, well, making an image of the OS?
Well, let’s see if I can explain. You start with a base image, and then make your changes, and commit those changes using docker, and it creates an image. This image contains only the differences from the base. When you want to run your image, you also need the base, and it layers your image on top of the base using a layered file system: as mentioned above, Docker uses AuFS. AuFS merges the different layers together and you get what you want; you just need to run it.
You can keep adding more and more images (layers) and it will continue to only save the diffs. Since Docker typically builds on top of ready-made images from a registry, you rarely have to “snapshot” the whole OS yourself.
Docker vs Virtual machine – Answer #2:
It might be helpful to understand how virtualization and containers work at a low level. That will clear up lot of things.
Note: I’m simplifying a bit in the description below. See references for more information.
How does virtualization work at a low level?
In this case the VM manager takes over the CPU ring 0 (or the “root mode” in newer CPUs) and intercepts all privileged calls made by the guest OS to create the illusion that the guest OS has its own hardware. Fun fact: Before 1998 it was thought to be impossible to achieve this on the x86 architecture because there was no way to do this kind of interception. The folks at VMware were the first who had an idea to rewrite the executable bytes in memory for privileged calls of the guest OS to achieve this.
The net effect is that virtualization allows you to run two completely different OSes on the same hardware. Each guest OS goes through all the processes of bootstrapping, loading kernel, etc. You can have very tight security. For example, a guest OS can’t get full access to the host OS or other guests and mess things up.
How do containers work at a low level?
Around 2006, people including some of the employees at Google implemented a new kernel level feature called namespaces (however the idea long before existed in FreeBSD). One function of the OS is to allow sharing of global resources like networks and disks among processes.
What if these global resources were wrapped in namespaces so that they are visible only to those processes that run in the same namespace? Say, you can get a chunk of disk and put that in namespace X and then processes running in namespace Y can’t see or access it. Similarly, processes in namespace X can’t access anything in memory that is allocated to namespace Y. Of course, processes in X can’t see or talk to processes in namespace Y. This provides a kind of virtualization and isolation for global resources.
This is how Docker works: Each container runs in its own namespace but uses exactly the same kernel as all other containers. The isolation happens because the kernel knows the namespace that was assigned to the process and during API calls it makes sure that the process can only access resources in its own namespace.
The limitations of containers vs VMs should be obvious now: You can’t run completely different OSes in containers like in VMs. However, you can run different distros of Linux because they do share the same kernel. The isolation level is not as strong as in a VM. In fact, there was a way for a “guest” container to take over the host in early implementations.
Also, you can see that when you load a new container, an entirely new copy of the OS doesn’t start as it does in a VM. All containers share the same kernel. This is why containers are lightweight. Also unlike a VM, you don’t have to pre-allocate a significant chunk of memory to containers because we are not running a new copy of the OS. This enables running thousands of containers on one OS while sandboxing them, which might not be possible if we were running separate copies of the OS in their own VMs.
Good answers. Just to get an image representation of container vs VM, have a look at the one below.
Docker isn’t a virtualization methodology. It relies on other tools that actually implement container-based virtualization or operating system level virtualization. For that, Docker was initially using LXC driver, then moved to libcontainer which is now renamed as runc. Docker primarily focuses on automating the deployment of applications inside application containers. Application containers are designed to package and run a single service, whereas system containers are designed to run multiple processes, like virtual machines. So, Docker is considered as a container management or application deployment tool on containerized systems.
In order to know how it is different from other virtualizations, let’s go through virtualization and its types. Then, it would be easier to understand what’s the difference there.
In its conceived form, it was considered a method of logically dividing mainframes to allow multiple applications to run simultaneously. However, the scenario drastically changed when companies and open source communities were able to provide a method of handling the privileged instructions in one way or another and allow for multiple operating systems to be run simultaneously on a single x86 based system.
The hypervisor handles creating the virtual environment on which the guest virtual machines operate. It supervises the guest systems and makes sure that resources are allocated to the guests as necessary. The hypervisor sits in between the physical machine and virtual machines and provides virtualization services to the virtual machines. To realize it, it intercepts the guest operating system operations on the virtual machines and emulates the operation on the host machine’s operating system.
The rapid development of virtualization technologies, primarily in cloud, has driven the use of virtualization further by allowing multiple virtual servers to be created on a single physical server with the help of hypervisors, such as Xen, VMware Player, KVM, etc., and incorporation of hardware support in commodity processors, such as Intel VT and AMD-V.
Types of Virtualization
The virtualization method can be categorized based on how it mimics hardware to a guest operating system and emulates a guest operating environment. Primarily, there are three types of virtualization:
- Container-based virtualization
Emulation, also known as full virtualization runs the virtual machine OS kernel entirely in software. The hypervisor used in this type is known as Type 2 hypervisor. It is installed on the top of the host operating system which is responsible for translating guest OS kernel code to software instructions. The translation is done entirely in software and requires no hardware involvement. Emulation makes it possible to run any non-modified operating system that supports the environment being emulated. The downside of this type of virtualization is an additional system resource overhead that leads to a decrease in performance compared to other types of virtualizations.
Examples in this category include VMware Player, VirtualBox, QEMU, Bochs, Parallels, etc.
Paravirtualization, also known as Type 1 hypervisor, runs directly on the hardware, or “bare-metal”, and provides virtualization services directly to the virtual machines running on it. It helps the operating system, the virtualized hardware, and the real hardware to collaborate to achieve optimal performance. These hypervisors typically have a rather small footprint and do not, themselves, require extensive resources.
Examples in this category include Xen, KVM, etc.
Container-based virtualization, also known as operating system-level virtualization, enables multiple isolated executions within a single operating system kernel. It has the best possible performance and density and features dynamic resource management. The isolated virtual execution environment provided by this type of virtualization is called a container and can be viewed as a traced group of processes.
The concept of a container is made possible by the namespaces feature added to Linux kernel version 2.6.24. The container adds its ID to every process and adding new access control checks to every system call. It is accessed by the clone() system call that allows creating separate instances of previously-global namespaces.
Namespaces can be used in many different ways, but the most common approach is to create an isolated container that has no visibility or access to objects outside the container. Processes running inside the container appear to be running on a normal Linux system although they are sharing the underlying kernel with processes located in other namespaces, same for other kinds of objects. For instance, when using namespaces, the root user inside the container is not treated as root outside the container, adding additional security.
The Linux Control Groups (cgroups) subsystem, the next major component to enable container-based virtualization, is used to group processes and manage their aggregate resource consumption. It is commonly used to limit the memory and CPU consumption of containers. Since a containerized Linux system has only one kernel and the kernel has full visibility into the containers, there is only one level of resource allocation and scheduling.
Several management tools are available for Linux containers, including LXC, LXD, systemd-nspawn, lmctfy, Warden, Linux-VServer, OpenVZ, Docker, etc.
Containers vs Virtual Machines
Unlike a virtual machine, a container does not need to boot the operating system kernel, so containers can be created in less than a second. This feature makes container-based virtualization unique and desirable than other virtualization approaches.
Since container-based virtualization adds little or no overhead to the host machine, container-based virtualization has near-native performance
For container-based virtualization, no additional software is required, unlike other virtualizations.
All containers on a host machine share the scheduler of the host machine saving need of extra resources.
Container states (Docker or LXC images) are small in size compared to virtual machine images, so container images are easy to distribute.
Resource management in containers is achieved through cgroups. Cgroups does not allow containers to consume more resources than allocated to them. However, as of now, all resources of host machine are visible in virtual machines, but can’t be used. This can be realized by running
htop on containers and host machine at the same time. The output across all environments will look similar.
How does Docker run containers in non-Linux systems?
If containers are possible because of the features available in the Linux kernel, then the obvious question is how do non-Linux systems run containers. Both Docker for Mac and Windows use Linux VMs to run the containers. Docker Toolbox used to run containers in Virtual Box VMs. But, the latest Docker uses Hyper-V in Windows and Hypervisor.framework in Mac.
Now, let me describe how Docker for Mac runs containers in detail.
Docker for Mac uses https://github.com/moby/hyperkit to emulate the hypervisor capabilities and Hyperkit uses hypervisor.framework in its core. Hypervisor.framework is Mac’s native hypervisor solution. Hyperkit also uses VPNKit and DataKit to namespace network and filesystem respectively.
The Linux VM that Docker runs in Mac is read-only. However, you can bash into it by running:
Now, we can even check the Kernel version of this VM:
# uname -a Linux linuxkit-025000000001 4.9.93-linuxkit-aufs #1 SMP Wed Jun 6 16:86_64 Linux.
All containers run inside this VM.
There are some limitations to hypervisor.framework. Because of that Docker doesn’t expose
docker0 network interface in Mac. So, you can’t access containers from the host. As of now,
docker0 is only available inside the VM.
Hyper-v is the native hypervisor in Windows. They are also trying to leverage Windows 10’s capabilities to run Linux systems natively.