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Containerization and Zero Downtime Deployment: Kubernetes Explained

Kubernetes is an open source platform for deploying and containerizing applications. It helps optimize resource utilization and reduce downtime during software updates. By deploying Kubernetes solutions, providers can, for example, update applications without shutting them down, resulting in a positive customer experience.

When it comes to whether the platform is worth using, the numbers speak for themselves. Currently, Kubernetes is being developed by a community of more than 2300 contributors. It is also being used by many companies, both large and small. America's top companies are also eager to adopt it, with more than half of the Fortune 100 companies using Kubernetes.

The history of Kubernetes dates back to 2014, when it was developed by three Google engineers: Joe Beda, Brendan Burns, and Craig McLuckie. Currently, the platform is managed by the Cloud Native Computing Foundation (CNCF), which is part of the Linux Foundation.

Kubernetes architecture basics

The basics of the Kubernetes architecture include three key elements: clusters, nodes, and pods. A cluster is a set of machines used to run containerized applications managed by Kubernetes. Each cluster must have at least one node.

A node is a physical or virtual worker machine that is managed by the control plane. A node can contain multiple Pods, and the control plane automatically schedules their execution on different nodes, taking into account the available resources on each node.

Pods are the smallest, indivisible units in the Kubernetes platform, representing a group of one or more application containers. They are created during deployment and are an integral part of the application architecture, providing shared disk space, IP address, and container runtime information.

Each node is accompanied by a kubelet that monitors whether containers are running in the pod, a network proxy server that manages network rules, and a runtime environment, most commonly Docker. The kubelet, which is an agent running on each node, monitors and manages the operation of the pods on that node, ensuring that they are in the correct state and have access to the resources they need.

Containerization vs. Virtual Machines

In the past, a common solution was Virtual Machines (VMs), where a physical machine could be divided into multiple virtual machines, each requiring its own operating system and application configuration. Containerization has changed this concept by allowing the runtime environment to be packaged along with the application. This eliminates the need to create a new system for each environment, and containers are independent and isolated, allowing multiple applications to run securely on a single machine.

Containerization increases deployment agility and simplifies architecture development, but it also brings new challenges, such as monitoring dozens or hundreds of running containers and their configurations. However, it also allows for efficient use of resources since the only requirement is the installation of a container runtime, most commonly Docker

Kubernetes - containerization

Here's how Kubernetes works: files pass through the platform, which then divides them into containers. Containers are independent units that can be launched and managed by Kubernetes.

Each container has only the resources and dependencies needed to run a specific process. As a result, if a piece of code freezes, only the relevant container is restarted, not the entire Virtual Machine, resulting in greater reliability and system flexibility.

Containerization also makes it easy to break applications into smaller, independent parts that can be called services. These application components can communicate with each other in a variety of ways, allowing for flexible architecture building and scaling. This makes it easier to deploy software in different test environments that span different clouds, operating systems, and device types.

Through containers, applications are coupled with their entire runtime environment, forming a bubble in which they can operate, contributing to efficient resource management and increased system performance.

Why is it worth using the Kubernetes platform?

The Kubernetes platform offers a number of benefits that make it attractive to organizations looking to effectively manage their applications.

One of these is automatic scaling. Using the Horizontal Pod Autoscaler (HPA) mechanism, the platform monitors the load on pods and automatically adjusts their number based on current demand. HPA relies on metrics such as CPU or memory usage, and configuring minimum and maximum pod numbers along with the target metric value enables precise application scaling adjustments.

Another benefit of using Kubernetes is that it is self-healing. The platform is able to autonomously repair attached images (that is, running container instances) by responding to application failures by automatically removing damaged instances and creating new ones, ensuring uninterrupted application operation.

Load balancing is also important. It allows traffic to be distributed across a number of containers, improving application availability and performance.

In addition, ease of updating and management are other benefits of Kubernetes. Declarative definitions allow users to focus on what they want to accomplish rather than how to accomplish it, simplifying application management and updates without downtime.

In summary, Kubernetes offers automated scaling, self-healing capabilities, load balancing, and easy updating and management, making it a compelling choice for organizations seeking efficient application management solutions.

Why should you learn Kubernetes?

Kubernetes is a powerful tool that sets a new standard for application management. It enables the implementation of advanced practices such as Zero Downtime Deployment, which eliminates the need to shut down systems and move users during updates. In addition, it is a popular and well-documented tool that has gained the recognition of a large community.

Containerization, the foundation of Kubernetes, enables faster application development through efficient container orchestration. Kubernetes also provides better scalability by automatically adjusting the number of machines based on load, ensuring that the application is always tailored to the user's needs.

Kubernetes' self-healing mechanisms automatically detect and resolve problems in the application environment, increasing system reliability and availability. In addition, Kubernetes simplifies the process of deploying and updating applications by taking a declarative approach to configuration, ensuring consistency between the actual and desired state of the application.

With all of these features, learning Kubernetes becomes critical for individuals looking to improve their application management and IT infrastructure skills.

Develop your Kubernetes skills  - join Comarch training today!

Kubernetes offers comprehensive solutions that can revolutionize the way organizations deploy and manage their IT services. With this tool, you can deploy applications faster, scale infrastructure more effectively, and ensure system reliability. If you're interested in mastering Kubernetes, sign up for Comarch training here!

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