Containerization is a lightweight alternative to full machine virtualization that involves encapsulating an application in a container with its own operating environment. This provides many of the benefits of loading an application onto a virtual machine, as the application can be run on any suitable physical machine without any worries about dependencies.

1. Containerization
Submitted by
Jatin Chauhan
Registration No:
11702228
Bachelor of Technology - CSE
School of Computer Science & Engineering
Lovely Professional University, Phagwara

2. What is a Container?
A standardized unit of software
Containerization is a lightweight alternative to full machine virtualization that involves
encapsulating an application in a container with its own operating environment. This
provides many of the benefits of loading an application onto a virtual machine, as the
application can be run on any suitable physical machine without any worries about
dependencies.
Containerization has gained recent prominence with the open-source Docker.
Docker containers are designed to run on everything from physical computers to virtual
machines, bare-metal servers, OpenStack cloud clusters, public instances and more.
The Google Way
From Gmail to YouTube to Search, everything at Google runs in containers.
Containerization allows our development teams to move fast, deploy software efficiently,
and operate at an unprecedented scale. Each week, we start over several billion containers.
We’ve learned a lot about running containerized workloads in production over the past
decade, and we’ve shared this knowledge with the community along the way: from the
early days of contributing cogroups to the Linux kernel, to taking designs from our
internal tools and open sourcing them as the Kubernetes project. We’ve packaged this

3. expertise into Google Cloud Platform so that developers and businesses of any size can
easily tap the latest in container innovation.
Containerization vs. Virtualization via Traditional Hypervisors
The foundation for containerization lies in the Linux Containers (LXC) format, which is a
user space interface for the Linux kernel containment features. As a result, containerization
only works in Linux environments and can only run Linux applications.
This is in contrast with traditional hypervisors like VMware's ESXi, Xen or KVM, wherein
applications can run on Windows or any other operating system that supports the
hypervisor.
Another key difference with containerization as opposed to traditional hypervisors is that
containers share the Linux kernel used by the operating system running the host machine,
which means any other containers running on the host machine will also be using the
same Linux kernel.
Difference Between Containers and Virtual Machines (VMs)
A Virtual Machine has the capability to run more than one instance of multiple OS’s on a
host machine without overlapping. The host system allows the guest OS to run as a single
entity. A docker container does not burden the system as much as a virtual machine, as
running an OS requires extra resources, which can reduce the efficiency of the machine.
Docker containers do not tax the system and use only the minimum amount of resources
required to run the solution without the need to emulate an entire OS. Since fewer
resources are required to run the Docker application, it can allow for a larger number of
applications to run on the same hardware, thereby cutting costs.

4. However, it reduces the isolation that VMs provide. It also increases homogeneity because
if an application runs on Docker on one system, then it will run without any hiccups on
Docker on other systems as well.
Both containers and VMs have the virtualization mechanism. But for containers, the
virtualization of the Operating System takes place; while in the latter, the virtualization of
the hardware takes place.
VMs show limited performance, while the compact and dynamic containers with Docker
show advanced performance.
VMs require more memory, and therefore have more overhead, making them
computationally heavy as compared to Docker containers.
How Does Containerization Actually Work?
Each container is an executable package of software, running on top of a host OS. A
host(s) may support many containers (tens, hundreds or even thousands) concurrently,
such as in the case of a complex microservices architecture that uses numerous
containerized ADCs. This setup works because all containers run minimal, resource-
isolated processes that others cannot access.
Containerization – Implementing DevOps

5. Let’s find out why containers are slowly becoming an integral part of the standard DevOps
architecture.
Docker has popularized the concept of containerization. Applications in Docker containers
have the capability of being able to run on multiple operating systems and cloud
environments such as Amazon ECS and many more. Hence, there is no technology or
vendor lock-in.
Docker Not the Only Containerization Option
Docker may have been the first to bring attention to containerization, but it's no longer
the only container system option. CoreOS recently released a streamlined alternative to
Docker called Rocket.
 And Canonical, developers of the Ubuntu Linux-based operating system, has
announced the LXD containerization engine for Ubuntu, which will also be
integrated with OpenStack.
 Microsoft is working on its own containerization technology called Drawbridge,
which will likely be featured in Windows Server and Azure in the future. And Spoon
is another Windows alternative that will enable containerized applications to be
run on any Windows machine that has Spoon installed, regardless of the
underlying infrastructure.
Software developers are benefited by containers in the following ways:
The environment of the container can be changed for better production deployment.
Quick startup and easy access to operating system resources.
Provides enough space for more than one application to fit in a machine, unlike traditional
systems. It provides agility to DevOps, which can help in switching between multiple
frameworks easily. Helps in running working processes more efficiently.

6. Elucidated below are the steps to be followed to implement containerization
successfully using Docker:
 The developer should make sure the code is in the repository, like the Docker Hub.
 The code should be compiled properly.
 Ensure proper packaging.
 Make sure that all the plugin requirements and dependencies are met.
 Create Container images using Docker.
 Shift it to any environment of your choice.
 For easy deployment, use clouds like Rackspace or AWS or Azure.
1. DevOps-friendly
Containerization packages the application along with its environmental dependencies,
which ensures that an application developed in one environment works in another. This
helps developers and testers work collaboratively on the application, which is exactly what
DevOps culture is all about.
2. Multiple Cloud Platform

7. Containers can be run on multiple cloud platforms like GCS, Amazon ECS (Elastic
Container Service), Amazon DevOps Server.
3. Portable in Nature
Containers offer easy portability. A container image can be deployed to a new system
easily, which can then be shared in the form of a file.
4. Faster Scalability
As environments are packaged into isolated containers, they can be scaled up faster,
which is extremely helpful for a distributed application.
5. No Separate OS Needed
In the VM system, the bare-metal server has a different host OS from the VM. On the
contrary, in containers, the Docker image can utilize the kernel of the host OS of the bare-
metal physical server. Therefore, containers are comparatively more work-efficient than
VMs.
6. Maximum Utilization of Resources
Containerization makes maximum utilization of computing resources like memory and
CPU, and utilize far fewer resources than VMs.
7. Fast-Spinning of Apps
With the quick spinning of apps, the delivery takes place in less time, making the platform
convenient for performing more development of systems. The machine does not need to
restart to change resources.
With the help of automated scaling of containers, CPU usage and machine memory
optimization can be done taking the current load into consideration. And unlike the
scaling of Virtual Machines, the machine does not need to be restarted to modify the
resource limit.
8. Simplified Security Updates
As containers provide process isolation, maintaining the security of applications becomes
a lot more convenient to handle.
9. Value for Money

8. Containerization is advantageous in terms of supporting multiple containers on a singular
infrastructure. So, despite investing in tools, CPU, memory, and storage, it is still a cost-
effective solution for many enterprises.
A complete DevOps workflow, with containers implemented, can be advantageous for the
software development team in the following ways:
 Offers automation of tests in every little step to detect errors, so there are fewer
chances of defects in the end product.
 Faster and more convenient delivery of features and changes.
 Nature of the software is more user-friendly than VM-based solutions.
 Reliable and changeable environment.
 Promotes collaboration and transparency among the team members.
 Cost-efficient in nature.
 Ensures proper utilization of resources and limits wastage.
How does Docker perform Containerisation?
Docker image containers or applications can run locally on Windows and Linux. This is
achieved simply by the Docker engine interfacing with the operating system directly,
making use of the system’s resources.
For managing clustering and composition, Docker provides Docker Compose, which aids
in running multiple container applications without overlapping each other. Developers
further connect all the Docker hosts to a single virtual host through the Docker Swarm
Mode. After this, the Docker Swarmis used to scale the applications to a number of hosts.
Thanks to Docker Containers, developers have access to the components of a container,
like application and dependencies. The developers also own the framework of the
application. Multiple containers on a singular platform, and depending on each other, are
called Deployment Manifest. In the meantime, however, the professionals can pay more
attention to choosing the right environment for deploying, scaling, and monitoring.
Docker helps in limiting the chances of errors, that can possibly occur during transferring
of applications.
After the completion of the local deployment, they are further sent to code repository like
Git repository. The Docker file in the code repository is used to build Continuous
Integration (CI) pipelines that extract the base container images and build Docker images.
The developers work on the transferring of files to multiple environments, while the
managerial professionals look after the environment to check defects and send feedback
to the developers.

9. Containerization or virtualization: What’s the right path for you?
Virtualization enables you to run multiple operating systems on the hardware of a single
physical server, while containerization enables you to deploy multiple applications using
the same operating system on a single virtual machine or server.
Virtual machines are great for supporting applications that require an operating system’s
full functionality when you want to deploy multiple applications on a server, or when you
have a wide variety of operating systems to manage. Containers are a better choice when
your biggest priority is to minimize the number of servers you’re using for multiple
applications.
Your use case matters too. Containers are an excellent choice for tasks with a much shorter
lifecycle. With their fast set up time, they are suitable for tasks that may only take a few
hours. Virtual machines have a longer lifecycle than containers, and are best used for
longer periods of time.
The way forward for your organization will depend on everything from the size of your
operations and workflows to your IT culture and skill sets. And, containerization and
virtualization technologies are coming together that could influence your decision
making.

10. Ultimately, virtualization and containerization may both have a place in your IT strategy.
Consider your ultimate goals, immediate use cases, and team skillset before setting down
a specific path.