Difference Between Docker vs VMs
Docker containers bring along with them numerous amounts of tags where it majorly aims to promote the cloud portability feature by running the same application in different virtual environments. Dockers are said to be the open platform for developers and are also a mechanism that is used to isolate the dependencies of each application by packaging them into a container. Containers are safer and scalable to use and deploy comparatively. Virtual machines make their extensive use in the field of cloud computing. Resource control and isolation are achieved by making use of VMs. Virtual machines load a complete operating system along with their own memory management, thereby enabling applications to be more secure and efficient without risking high availability. This is done as all the valuable resources are emulated for the hypervisor and guest operating system. Many instances can be hosted on a single machine in parallel on possibly one or many operating systems, and every guest OS runs as an individual entity from the host system.
Head To Head Comparison Between Docker and VMs (Infographics)
Below is the Top 6 difference between Docker and VMs:
Key Differences Between Docker and VMs
Let us discuss some of the major differences between Docker and VMs:
Docker containers make use of docker engine where a single kernel is responsible for the execution of the same application across different operating systems by making use of image present inside containers which is ready to be deployed in no time, whereas in the case of virtual machines, a hypervisor is used which is a firmware, software, and hardware which is also known as VMM (virtual machine monitor). It presents the Virtual machine or the guest operating system, a virtual operating platform used for managing and executing the guest operating system efficiently. A number of instances from a wide variety of operating systems can share the virtualized hardware resources such as Linux, macOS, and Windows. All of this can run on a single physical x86 based machine.
Docker containers are weaker than Virtual Machines on one parameter, which is related to Isolation. Intel’s VT-x and VT-d technologies have their virtual machines backed with ring-1 isolation, which helps its virtual machines from clashing and interfering with the working of one another, whereas Docker containers still don’t have any isolation mechanism, thereby making them more prone to exploits.
Containers are way too fast, secure, light-weighted, and reliable for as long as the user is planning to stick with a single platform to provide a shared operating system. A container can be launched in a few seconds at max, whereas it can take up to several minutes for a virtual machine to launch. Containers are known for superior performance compared to running an application inside a virtual machine.
Not many digitally operational companies are interested in making Virtual Machines as their primary choice and are migrating towards the use of containers as application deployment is comparatively lengthy and running microservice is also a major challenge it poses. There are still some, like Starling Digital bank, which uses VMs over Dockers, whereas most of the companies interested in enterprise-grade security for their infrastructure prefer to make more use of Dockers.
Docker containers can be shared across a number of team members, thereby bringing portability to the development of the application. This is one of the major breakthrough points for the DevOps team. It also becomes a less painful task for the developers as the application created doesn’t come out to be platform-dependent and system-specific. The given specifications and configurations also make the deployment much more convenient, easy and fast. In contrast, you can have a docker running inside a Virtual machine once it is up and running, and the containers would run inside the virtual machine itself, an age-old method. Therefore we can safely assume that they are not mutually exclusive and can co-exist along with each other.
Docker and VMs Comparison Table
Below is the topmost comparison between Docker vs VMs.
Basis of Comparison |
Dockers |
Virtual Machines |
Boot-Time | Dockers can boot in seconds | It often takes minutes for VMs to boot |
Execution | Makes use of execution engine | Makes use of a hypervisor |
Memory | More memory efficient as no space needed to virtualize | Less memory efficient as the entire OS needs to be loaded before starting the service |
Isolation | No provision for isolation of systems and hence are more prone to adversities. | Efficient isolation mechanism and hence interference possibility are less. |
Ease of Deployment | Deploying through dockers is extremely easy as only one image, containerized, can be used across different operating systems. | Deploying in Virtual Machines is a comparatively lengthy process where separate instances are responsible for the execution. |
Ease of Usage | Dockers have a comparatively complex usage mechanism that consists of both third-party and docker-managed tools. | The tools associated with a VM are comparatively easier to use and simpler to work with. |
Conclusion
Dockers are quickly gaining huge popularity in the ecosystem, but I believe some use cases where VMs are a better choice anyway. Virtual machines today are a better fit for the production environment when compared with Docker containers. Therefore, Dockers cannot be said to be the replacement of Virtual machines but an add-on, at least for now. Know about the companies’ architecture and the application needs and decide what to adopt. Stay tuned to our blog for more articles like these. Docker containers, on the other hand, make use of a docker engine instead of making use of the hypervisor, thereby making containers small, less isolated, better compatibility, high performance-intensive, and quick responsiveness is achieved as compared to VMs as the host’s kernel is shared. They have the capability to share a single kernel and application libraries. The overhead is comparatively lower than that of the Virtual machines. Companies today are making use of a hybrid approach mostly as the choice among the two is also dependent on the kind of workload being offered, application design.
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