Containers and Virtual Machines are both Virtualization technologies that can be used to deploy and manage applications. However, they have different strengths and weaknesses, and the best choice for a particular application will depend on a number of factors.
Containers are lightweight and efficient, making them ideal for deploying microservices-based applications. They are also portable, meaning that they can be easily moved from one environment to another. However, containers do not provide as much isolation as virtual machines, and they can be more difficult to manage.
Virtual Machines are more heavyweight than containers, but they provide a higher level of isolation and security. They are also easier to manage, as they can be managed using traditional tools like Hypervisors. However, virtual machines can be more resource-intensive than containers, and they can be less portable.
In this guide, we will discuss the key differences between containers and virtual machines in more detail. We will also provide some guidance on when to use each technology.
Table of Contents
Every tool or platform is created to solve a particular problem. You have to first understand the problem statement and what solution virtualization provides.
Virtualization is the process of creating a virtual version of a hardware resource, such as a server, storage device, network, or even an entire operating system.
Before the invention of virtualization, you had to buy physical hardware which includes DRIVES, RAM, CPU, GPU, etc., to install an operating system.
And then you have to install the operating system on top of the hardware, harden it as per your personal requirement or industry standards, and then hand it over to the development team. This is a time-consuming and resource-consuming process.
Virtualization is created to address this issue. Virtualization allows you to use the same physical resources from a single machine to create multiple machines called virtual machines.
This allows multiple instances of the resource to run on the same physical hardware, which can improve efficiency and save costs.
The following image will give you a good idea of installing operating systems with and without virtualization.
Virtualization offers a many benefits and solves a number of problems, including:
A Hypervisor is a software that will be installed on top of your operating system or hardware. It allows you to create multiple virtual machines by isolating the underlying physical resources and allocating them to multiple virtual machines.
There are two types of hypervisor:
This type of hypervisor is installed directly on top of the physical hardware and there is no need of installing any operating system on top of the hardware.
The hypervisor will directly interact with the hardware and allocate resources to the virtual machines you create. This type of hypervisor is most commonly used in corporations.
Some of the popular type 1 hypervisors are
This type of hypervisor is used mostly on your personal computers to create virtual machines. Type 2 hypervisors come as software that needs to be installed on top of an operating system.
Type 2 hypervisors are slow compared to Type 1 hypervisors because the Type 2 hypervisors need to interact with the OS and then with the physical resource, but Type 1 hypervisors directly interact with the physical resources.
Some of the popular type 2 hypervisors are
There are many factors to be considered before choosing the right hypervisor solution.
If you are looking for a free hypervisor to quickly spin up some virtual machines for testing purposes, then Oracle Virtualbox and VMware workstation will be a perfect choice. Both hypervisors are available for Windows, Linux, and macOS platforms.
If you are using Linux as your base operating system, then KVM will be a preferred choice. Since KVM is integrated with Linux kernel, it out-performs Virtualbox, VMWare workstation and other Type-2 hypervisors.
In most cases, the companies will go with Type 1 hypervisors for production deployments. You can purchase the Type 1 hypervisor licenses which also come with support.
In any case, if you face issues, the product support team will assist you in fixing them. This is not the case with freeware hypervisors.
For freeware hypervisors, you should rely on community support or product articles to fix any issues.
In the context of computing, virtualization refers to the creation of a virtual machine (VM). A VM is a software-based computer that runs on top of a physical machine. It has its own operating system, memory, storage, and network resources.
The physical machine is also called as host machine and the virtual machine is known as guest machine.
As an example, let's say you buy either a Server machine or a Laptop and install your favorite operating system. You can then install any virtualization tools (E.g. Oracle Virtualbox) and create one or more guest operating systems (VMs) without buying dedicated hardware for each operating system.
The following image shows my current virtualization setup. I am running my favorite Pop!_OS Linux distribution as my base operating system. I am using Virtualbox as the virtualization solution and running Fedora XFCE as a virtual machine.
Here,
Virtualization plays a crucial role in cloud computing. The resource you spin up on the cloud platforms is created virtually in the cloud provider's data center. For example, let’s talk about AWS which is one of a popular cloud platform in the market.
AWS uses KVM as its virtual solution. When you launch an EC2 instance in AWS, it actually creates a virtual machine through KVM. When it comes to the cloud along with virtualization automation also plays a major role.
In traditional data centers, we create virtual machines manually but in the cloud environment, everything happens in a minute or so with the help of automation.
The main advantage of virtualization on the cloud platform as an end user who handles IAAS, PAAS, or SAAS environments is we need not worry about physical hardware and setting up type 1 or type 2 hypervisors. All we care about is spinning up an EC2 instance or any other services quickly.
Virtualization is not only about servers in the cloud. Storage, network, CPU, GPU, Desktops, etc. are also virtualized in the cloud. As you know, the cloud offers three main service types.
Containers are a more simplified solution for creating and deploying modern-day applications. Containers play well with any DevOps stack you choose to create and deploy applications. Containers are mostly used to create applications with microservices architecture.
Unlike the Virtual machines, Containers will not host the full operating system. Containers are packaged only with the necessary libraries and services that are essential to run an application.
Containers use the underlying operating system’s kernel to access hardware resources through the kernel and provide isolation between containers through Namespace and CGroups.
Similar to hypervisors in virtualization, you need to install any of the container management solutions like Docker, Podman, etc., to work with containers.
The most popular container management solution is Docker which can be used to run your test applications as well as production workloads.
So how is the container set up?
Below is a sample image where I pulled the Python latest image from the Docker Hub and launched the container. I managed to set up the Python environment I required with just two commands, and it was faster than installing Python directly on my main machine.
Till now I gave you a very simplified explanation of Containers and Container management solutions. Now let’s dive deep into the two technical aspects of containerization.
Container runtimes are responsible for spinning up your containers, allocating required resources, setting up namespaces, unpacking the image, managing the image, etc.
There are high-level and low-level container runtimes. Low-level runtimes talk with the kernel and provide resource allocation and process isolation.
In 2015, an initiative named Open Container Initiative (OCI) was created by industry leaders with the primary focus of creating a standard format for containers and run times.
OCI develops a runtime called runc. The container orchestration tools that you see in the market now are created with runc as the base. That is why some container solutions are cross-compatible. For example, podman will seamlessly allow you to run docker containers.
Namespace and CGroups are kernel features that actually made the implementation of containerization possible.
Namespace is a kernel feature that provides isolation between different processes. There are different namespaces offered by the Linux kernel. For example, there is a user namespace that has its own user and group id that will be allocated to the process.
There is also one other namespace called process ID which allocated PID to the process in a namespace. The PID from two different namespaces will be independent of each other.
This set of features allows the containers to run on their own namespace thus preventing conflict between container processes.
CGroup, aka control group, is a kernel feature that allows you to limit the number of resources (RAM, CPU, DISK IO, NETWORK) a specific process can access.
When you create containers the low-level run time talks to the kernel Cgroups and makes sure only a specified amount of resource is allocated to the container and not beyond that.
Most software development approaches now focus on Agile and DevOps for incremental and quicker deployment of applications.
DevOps is a set of tools, frameworks, and best practices to help deliver the product in incremental chunks. You can use any set of tools to form your DevOps stack to build and deploy your application.
Microservices is another popular approach in software development where you build independent software services and then it will communicate with other services over the network through API. Containers are the center of the microservices implementation where you deploy a service in a container.
For example, let’s say you are building a front-end application and currently working on authentication services for the application. The authentication services allow the user to create accounts or log in using existing accounts for your product.
In this case, you can deploy the authentication service to a docker container which then communicates with the backend database which will also be running in a different container.
Following will be the flow when you are using DevOps to deploy an application.
Container solutions like Docker, Podman, and CRI-O offer tools to pull images, launch one or more containers, and start and stop containers.
This is most suitable for a single-user approach. When it comes to the real world, there are many aspects to container deployment.
We cannot manually satisfy the above aspects when working with real-life applications. so we need a tool that can automatically take care of the above aspects.
The Orchestration tools are responsible for communicating with underlying container solutions like Docker and handling the life cycle of the container.
Some of the core functionality of an orchestration tool is:
There are some popular container orchestration engines like Docker Swarm, Kubernetes, and Apache Mesos.
Among these three, Kubernetes is the very popular and advanced solution used in enterprise to deploy highly scalable and available applications.
The majority of the cloud providers offer kubernetes as PAAS solutions and they are tightly integrated with their native DevOps stack for seamless application prototyping, development, and deployment.
Here's a comparison between Containers and Virtual machines:
| Aspect | Containers | Virtual Machines |
|---|---|---|
| Isolation | Lightweight isolation from host and other containers. | Strong isolation, simulating separate physical machines. |
| Resource Efficiency | Shares host OS kernel, uses less memory and disk space. | Requires separate OS for each VM, consumes more resources. |
| Startup Speed | Extremely fast startup times. | Slower startup times due to OS boot. |
| Performance | Near-native performance, lower overhead. | Slightly higher overhead, may impact performance. |
| Portability | Highly portable due to shared OS kernel. | Less portable due to OS differences. |
| Scalability | Easily scalable, as containers share host resources. | Can be resource-intensive to scale due to multiple OS instances. |
| Isolation Type | Process-level isolation using namespaces. | Full machine-level isolation. |
| Use Cases | Microservices, DevOps, and cloud-native apps. | Legacy applications, different OS instances. |
| Management | Managed using orchestration tools like Kubernetes. | Managed using virtualization management tools. |
| Density | Can run multiple containers on a single host. | Limited number of VMs per host due to resource consumption. |
| Security | Limited isolation, potential security challenges. | Strong isolation, better security for each VM. |
Keep in mind that the choice between containers and virtual machines depends on the specific use case and requirements of your project.
A: Containers are lightweight, standalone executable software packages that bundle applications and their dependencies. Virtual machines (VMs) are software-based emulations of physical computers that run operating systems and applications.
Q: How do containers differ from virtual machines?A: Containers share the host OS kernel and resources, resulting in lower overhead and faster performance. Virtual machines, on the other hand, run separate OS instances and have stronger isolation, which can lead to higher resource consumption and slower performance.
Q: What's the key benefit of containers?A: Containers offer excellent portability and consistency across various environments, making application deployment and scaling easier. They are ideal for microservices architecture and cloud-native applications.
Q: When should I use virtual machines?A: Virtual machines are suitable for scenarios requiring stronger isolation, such as legacy applications, different operating systems, and when security is a top concern. They provide a more traditional approach to virtualization.
Q: Which is more resource-efficient, containers or virtual machines?A: Containers are more resource-efficient as they share the host's kernel and resources. This enables higher density and better utilization of hardware compared to virtual machines that require separate OS instances.
Q: Are containers or virtual machines more secure?A: Virtual machines offer stronger security through complete isolation, ensuring that any vulnerabilities are contained within the VM. Containers share the host kernel, which can present potential security challenges if not managed properly.
Q: What tools are used to manage containers and virtual machines?A: Containers are often managed using orchestration tools like Kubernetes and Docker Swarm. Virtual machines are managed using virtualization management tools like VMware, VirtualBox, and Hyper-V.
Q: Can containers and virtual machines work together?A: Yes, containers and virtual machines can complement each other in certain scenarios. For instance, you can run containers within virtual machines for added isolation or to run different types of applications in distinct environments.
Q: Which platforms support containers and virtual machines?A: Both containers and virtual machines are supported on various platforms, including Windows, Linux, and macOS. Docker, Podman, Kubernetes, and Docker Swarm are popular for containers, while KVM, VMware, VirtualBox, and Hyper-V are well-known for virtual machines.
Q: Which technology is better for scaling applications?A: Containers are generally better suited for scaling applications due to their lightweight nature, rapid startup times, and efficient resource sharing. They are designed to work seamlessly with container orchestration platforms like Kubernetes.
If you're new to the world of software and looking to choose the right Virtualization and Containerization tools to begin with, my suggestion is to start using VirtualBox for creating virtual machines and Docker for handling containers. These tools are available for Windows, Linux, and macOS operating systems.
There is also a popular tool called Vagrant that lets you spin up virtual machines in virtualbox and other providers in an automated way.
This will remove the overhead of installing OS in the VM instead all you have to do is create a vagrant config file and run a single command to provision the VM.
We have reached the end of the article and by now you should have a fair idea about virtual machines and containers.
In summary, Containers are a good choice for applications that need to be lightweight and portable, while Virtual Machines are a good choice for applications that need to be isolated and secure.
The choice ultimately depends on your specific needs, with containers optimizing resource usage and virtual machines ensuring strong separation.
One can learn these two technologies to further increase their domain knowledge and enhance job opportunities in the field of IT infrastructure, cloud computing, software development, DevOps, and modern application deployment.
By mastering containers and virtual machines, individuals can position themselves as valuable assets in a variety of roles related to system administration, software engineering, cloud architecture, and more.
The above is the detailed content of Containers Vs Virtual Machines: A Detailed Comparison. For more information, please follow other related articles on the PHP Chinese website!
![[Web front-end] Node.js quick start](https://img.php.cn/upload/course/000/000/067/662b5d34ba7c0227.png)
