What is containerization ?

Defining Containerization

Containerization is a cloud operating system virtualization that allows multiple isolated user-space instances to run on a shared operating system kernel.

Each cloud container acts as a self-contained unit, encapsulating an application and all its dependencies, including libraries, binaries, and configuration files.

This isolation ensures that cloud applications running within different containers do not interfere with each other, providing consistency and predictability across diverse environments.

Starting With Virtualization

While the developer knows his application and its dependencies best, it is usually a system administrator who provides the infrastructure, installs all of the dependencies, and configures the system on which the application runs. This process can be very error-prone and hard to maintain, so servers are only configured for a single purpose like running a database or an application server and then get connected by network.

To get more efficient use out of the server hardware, virtual machines can be used to emulate a full server with CPU, memory, storage, networking, operating system and the software on top. This allows running multiple isolated servers on the same hardware.

From Virtualization to Containerization

Before the widespread adoption of containers, server virtualization was the most efficient way of running applications isolated and easy to handle. But given that virtualization requires running the whole operating system including the kernel, it always comes with some overhead if you need to run a lot of servers.

Containers can be used to solve both of these problems, managing the dependencies of an application and running much more efficiently than spinning up a lot of virtual machines.

Why Containerization Matters

Containerization offers many benefits that speed up DevOps and improve computer resource usage. Today, containers are essential to modern software development, and these are some of the reasons for that:

• Portability: Containers are highly portable and can run consistently on different platforms and infrastructures – they can be run anywhere, eliminating the "it works on my machine/platform only" problem.
   
• Efficiency: Containers share the host operating system kernel, which, compared to standard virtualization, makes them very lightweight and efficient in terms of resource utilization and DevOps speeds.
   
• Scalability: Containers can be easily scaled up or down to accommodate changing workloads, enabling efficient resource management – and giving companies flexibility when running workloads.
   
• Faster deployment: Containers' lightweight nature allows for faster startup times and rapid cloud deployment, accelerating the software development lifecycle. Their flexibility also aids scalability, allowing for on-the-fly DevOps decisions.
   
• Microservices architecture: Containerization aligns seamlessly with microservices architecture. With microservices, developers can decompose apps into more minor, independent services that are developed, deployed, and scaled independently.

Difference Between Containers and Virtual Machines

While both containers and virtual machines offer virtualization, there are fundamental differences. These differences come down to architecture and the way the architecture impacts resource utilization.

Containers provide process-level isolation on a shared operating system kernel, making them lightweight and highly portable.  Virtual machines, on the other hand, offer full hardware virtualization with a guest operating system, resulting in heavier resource usage and less portability.

The net result is that cloud containers boast faster startup times than virtual machines. VMs require a complete guest operating system boot process, which takes longer and consumes more resources.

For use cases, containers excel in DevOps microservices and cloud-native applications, while virtual machines are more commonly used for legacy applications and environments requiring diverse operating systems – even though you could dedicate an entire VM for a cloud native app, a container may be more efficient.

Demystifying Containers

Containers have become the cornerstone of modern cloud application development, offering a lightweight and efficient way to package, distribute, and run applications.

However, containers in the cloud are complex. Understanding how containers work can be daunting and require a fair bit of learning. Here, we will try to demystify containers by exploring their core components and how they function.

What Makes a Container?

At its core, a container consists of three essential elements:

• Code: Code is correct at the heart of the container, containing the application's source code (also known as the executable files).
   
• Runtime: The runtime is responsible for executing the cloud application code within the container. It provides a controlled environment where the application can run without interfering with other processes on the host system.
   
• Libraries: Libraries are collections of pre-written code that provide functionalities not built into the application itself. We always need libraries because these chunks of plug-in code are essential for the application to run correctly and perform specific tasks.

Finally, most cloud application containers will have a list of dependencies outside the container. These dependencies are external chunks of code an application will rely on to function. These can include other libraries, system tools, or even other containers.

How Container Images Function As Blueprints

A container image is a static snapshot of a container, capturing its code, runtime, libraries, and dependencies.

This image is a blueprint for creating multiple identical containers to host: it’s a fast way to copy and paste containers. Images help ensure containers are consistent—something called reproducibility, ensuring everything is the same in different environments.

Think of it as a DevOps recipe book that can create multiple copies of the same dish with the same taste and quality.

Container images are typically stored in cloud application registries. Both Docker Hub and the increasingly popular Harbor are examples of a container registry, which makes it easy for users to pull and run a container on their systems.

When a container image is run, a new container is created based on the image's specifications. This process resembles following a recipe to create a new dish from scratch.

Steps To Container Adoption

As mentioned before, containerization is powerful but quickly becomes complex. Careful consideration and planning is at the core:

The first step in container adoption is selecting the right container platform that aligns with your organization's needs and goals. Several popular container options are available, each with its own strengths and use cases.

That said, Docker will likely be at the top of your cloud container applications list. It is the widely adopted container platform that simplifies the process of building, shipping, and running containers. Docker container infrastructure is known to be user-friendly, and it also comes with documentation that can help companies that are not that familiar with containerization.

Besides, with Docker as a host, you get a truly vast cloud application ecosystem of tools and resources. Docker is an excellent choice for developers who want to start with containers quickly and easily.

Nonetheless, as your workload grows, you’ll need something to help you manage your containers – because they’re likely to grow to hundreds or thousands in number. Kubernetes is possibly the choice -source platform for automating the deployment, scaling, and management of containerized applications. Kubernetes makes it far easier to go through the process of managing complex container clusters.

Considering Container Security

Container security is a critical component of Linux cloud security, ensuring applications and data protection within containerized environments. You must apply host security measures at every stage of the container lifecycle, applying security principles from development and deployment to runtime.

This includes secure container image builds, security vulnerability scanning, security access controls, and continuous monitoring of container activity for security anomalies. By prioritizing container security, you mitigate security risks associated with container security vulnerabilities.

Finally, you may need another container usability and control layer: Rancher is the tool you should consider, especially if your Kubernetes instances become very complex. Rancher also supports security objectives.

Finally, with containerization security evolving rapidly, your business must continue to train and educate to ensure that developers and operations teams have the necessary skills to work with containers effectively.

As you can see, containers are now used everywhere. Indeed, most complex computing environments will now use containers – just as VMs used to be a staple of computing environments.