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Containers and Kubernetes

Packing for Your Cloud Journey: Containerization Explained

By Leah Zitter | September 27, 2021

With companies migrating resources to the cloud and adopting cloud-native technologies at an accelerating rate, containerization is becoming a new term of art. For organizations and users just beginning or still planning their cloud journeys, the term can be obscure. Containerizing on the cloud is a developing practice, but it's based on simpler concepts anyone can recognize.

Think of software containers as IT shipments that bundle each application and its runtime environment into a standalone, executable package. These containers move from environment to environment - across testing, staging and production infrastructures. They're lightweight, fast, scalable and secure, preventing software flaws from slipping out and affecting the environment. With attributes like these, containers are ideal for hosting data and software on the cloud.


The Origins of Containerization


Early on, organizations ran applications on multiple physical servers, but these were costly and difficult to maintain, prompting developers to turn to virtualization. Virtualization allows applications and their components to run on the same physical server in isolated virtual machines (VMs). 

Containers are similar to VMs but, unlike VMs, are decoupled from the server's underlying  physical infrastructure and are, therefore, more lightweight, making them portable across clouds and open-source distributions. Put another way, rather than having separate open-source guests on the host server like VMs, containers share that same open-source kernel. This makes them cheaper and simpler to use, enabling developers to simply "carry" their software tools from one environment to another, instead of recreating these containers from scratch.


What is Containerization?


Containerization refers to packaging software code and its components in single "containers". When and how resources are containerized can depend on a number of factors:

  • Runtime tools

  • System tools

  • System libraries

  • Settings

Multiple containers can be employed across a single operating system (OS) and share that same open-source kernel, which helps them run consistently in any environment and across any infrastructure, regardless of that infrastructure's OS. For example, containers make it possible to transfer code from a desktop computer to a virtual machine (VM) or from a Linux to a Windows operating system, and to transfer that same code with its dependencies to public, private or hybrid clouds. 

Numerous benefits account for the popularity of containerization as a solution. Containers are:

  • Far more agile, efficient and portable than VMs. 

  • Perfect for continuous development, integration, and deployment with quick and efficient rollbacks.

  • Cheaper than VMs.

  • Extremely fast.

  • Easy to manage.

  • Constant across OS environments; they run the same on laptop as they do in the cloud.

  • Extremely secure due to their isolated nature.


What Applications and Services Are Commonly Containerized?


Some computing paradigms especially suit containerization, including:

  • Microservices, whereby developers can bundle single functions of their tasks into customized "packages". 

  • Databases, whereby each app is given its own database, eliminating the need to connect all to a monolithic database.

  • Web servers that need only a few lines of command on a container.

  • Containers within VMs, which save hardware space, augment security, and talk to specific services in the VM.


Examples of Containers


Docker is one of the most popular containers due to its speed, execution and holding power. Some other popular containers include:

  • CoreOS rkt

  • Mesos Containerizer

  • LXC Linux Containers

  • OpenVZ

  • CRI-O


Containerization orchestration


As more containers are used, enterprises will need systems to run them. Kubernetes, the most prominent container orchestration platform, helps control, monitor, and maintain your containers at massive scale.

Google Cloud offers its own containers to standardize software deployments across multiple machines and platforms. (This book provides a helpful guide). Google Kubernetes Engine helps IT teams manage troops of containers and automate software deployment.

Have you worked with containers before? Can you think of any points you'd like to add? Reach out and let us know!


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