If we compare containers with the VMs then we will find that Containers are faster as it uses the host OS kernel. There is no overhead of starting the whole operating system in case of Container. The container application start in matter of second, while VM requires whole operating system to load.
Are containers faster than VMs?
Yes Container are faster than VM.
Yes, containers have a better impact on virtualization, in some sense. But in other ways, it's still hard to tell really whether containers (and their "hypervisor" cousins such as iSCSI and KVM ) are faster in production environments.
My own experience comparing performance using containers to bare metal VMs indicates that containers require no more overhead than bare metal VMs (and are, in fact, faster on the bare metal side) ? even though containers can be more complex to setup and use, and are harder to troubleshoot.
However, if you know the difference between containers and bare metal VMs, then the above discussion may still apply. For example:
VMs have to be deployed with a cluster as the root container, whereas containers can be started and managed remotely via an API.
The primary benefit of containers is that they have much less overhead:
A container requires only a few CPU and disk resources, which is the same as a standalone VM.
There is a much lower need for CPU (no need for virtualization), as compared to VMs.
You don't need to worry about having a lot of disk space or bandwidth for a container's storage.
There's much less contention for resources (CPU, disk) among containers ? which in turn makes it possible to share one (or several) VMs across many systems.
In short, unlike VMs, containers have no overhead while running, but the overhead is much lower as compared to bare metal, and can have a significant impact on system throughput.
Are containers better for some applications?
Yes, they are. But not for all applications.
Because a number of features and capabilities in containers make it better for certain workloads than bare metal VMs, the above discussion may still apply to "premium" workloads such as those which can handle virtualization, network overhead, and other issues as well as for "lower" throughput applications.
I could see an argument (arguably in the same way as for VM usage) for the use of containers inside of "conventional" clouds, where VMs can be used to provision resources.
If you really need performance beyond a bare metal VMs, then containers will probably be faster at handling other concerns like bandwidth, latency, etc.
Kubernetes is popular container orchestration tool, which is very popular. Let?s see the features of Kubernetes:
Automatic provisioning: If you want to provision/manage an entire cluster on a single machine, then Kubernetes provides you with a way to schedule builds to run based on certain criteria, with a minimum amount of downtime. Using an "Auto Deploy" or "Self-Deployment" option has become one of Kubernetes' most popular options.
When deploying from the cluster: Since all nodes are part of a "cluster" using Kubernetes, then when you start Kubernetes, the host machines are automatically started and configured on the cluster itself. Therefore, it's possible to deploy and run on almost any device of any size ? whether it is a VPS, a virtual machine, or an embedded device ? provided that it can accept a specific Kubernetes version installed.
Since all nodes are part of a "cluster" using Kubernetes, then when you start Kubernetes, the host machines are automatically started and configured on the cluster itself. Therefore, it's possible to deploy and run on almost any device of any size ? whether it is a VPS, a virtual machine, or an embedded device ? provided that it can accept a specific Kubernetes version installed. Resource monitoring: Kubernetes provides more efficient metrics for managing/performing tasks in the cluster, and can be used to ensure that resources aren't being wasted.
Kubernetes provides more efficient metrics for managing/performing tasks in the cluster, and can be used to ensure that resources aren't being wasted. Dynamic provisioning: Every time you add a virtual machine to a cluster, you are automatically provisioned with up to a certain number of Kubernetes nodes. This enables you to have a cluster without having to run configuration changes across all your virtual machines everytime you add/remove a node in the cluster. Kubernetes provides automatic provisioning with one click or on a per-VPC basis, either on a per-container basis or per-IP/TCP basis.
Check Docker tutorials at:
Hope above information helps you.