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Kubernetes is a flexible, scalable, and open-source platform for managing services and applications that run on containers, which facilitates both automation and customization. It is one of the most popular and largest growing networks. Its support and tools are extensively available.
Kubernetes was open-sourced by Google in 2014 and is a combination of over 15 years of Google’s experience in running production workloads at scale with a lot of innovative ideas and practices from the community.
The era of traditional deployment: In the early days, companies used to run applications on physical servers. It doesn’t allow to set resource limits for applications on physical servers, causing resource allocation issues.
For example, if multiple applications are running on a physical server, there may be an instance of the application that consumes most of the resources, making others slow. The solution is to run a single application on a different physical server. Due to the underutilization of resources, it costs companies a lot of money to maintain many physical servers.
The era of virtualization implementation: Virtualization was introduced to solve this problem. It permits you to run various virtual machines (VMs) on the CPU of a single physical server. Virtualization allows you to isolate applications between virtual machines and provides a level of security because other applications cannot freely access information in an application.
Virtualization makes better use of resources on physical servers and enables better scalability because applications can be easily added or upgraded, reduce hardware costs, etc. Virtualization allows you to present a set of physical resources as a cluster of virtual machines at once.
Each VM is a complete machine running all components on top of virtualized hardware, including its own operating system.
The era of Container Deployment: Containers are similar to virtual machines, but have relaxed isolation properties for sharing operating systems between applications.
Therefore, the container is considered light. Similar to VM, containers have their own file system, CPU, memory, process space, etc. Isolated from the underlying infrastructure, they can be ported through the cloud and OS distributions.
Containers become popular because they provide additional benefits such as:
- Create and deploy agile applications- Creating container images is easier and more efficient than using VM images.
- Continuous development, integration, and deployment- Provides reliable and frequent container image creation and deployment via quick and easy rollback.
- Action separation and development issue- Create an application container image in build/publish instead of an application container image at deployment time, thus separating the application from the infrastructure.
- Observability shows not only OS-level information and metrics but also the state of the application and other signals.
- Developing, testing, and production environment consistency- Run on laptops the same way it runs in the cloud.
- Portability of distribution in the cloud and operating system- Runs on Ubuntu, RHEL, CoreOS, on-premise, large public clouds and anywhere else.
- Application-centric management- Increase the level of abstraction, from running the operating system on virtual hardware to running applications on the operating system using logical resources.
- Loose, distributed, elastic and released microservices- Applications are divided into smaller separate parts and can be dynamically deployed and managed, rather than monolithic stacks running on a large single-use machine.
- Resource isolation- Predictable application performance
- Resource utilization: High efficiency and density.
Why do you need Kubernetes?
Containers are a good way to group and run applications. In a production environment, you must manage the containers running your application and ensure that there is no downtime. For example, if one container fails, another container must be started. By a system?
That’s how Kubernetes came to the rescue! kubernetes takes care of scaling and failover of your application, provides deployment modes, etc.
Service Detection and Load Balancing- Kubernetes can expose a container using a DNS name or using its own IP address. If traffic reaches the container, the kubernetes can load balance and distribute network traffic, which makes the deployment stable.
Storage Organization– Kubernetes allows you to automatically install storage systems of your choice, such as local storage, public cloud providers, etc.
Automatic rollback and deployment- You can use kubernetes to describe the desired state of the deployment container, and you can change the actual state to the desired state at a controlled speed. For example, you can automate kubernetes to create new containers for deployment, delete existing containers, and use all your resources for new containers.
Automatic packing of the box– You tell kubernetes how much CPU and memory (RAM) each container needs. kubernetes can put containers in nodes to make the best use of their resources.
Self-healing- Kubernetes restarts failed containers, replaces containers, removes containers that do not respond to user-defined health checks, and does not disclose them to the customer until the customer is ready to serve.
Key management and configuration– It allows you to store and manage sensitive information such as passwords, oauth tokens and ssh keys. You can deploy and update secret and application configurations without rebuilding container images or exposing secrets in stack configurations.
Generic terminology to better understand Kubernetes
Master: Control Kubernetes node machine. This is the source of all assignments.
Nodes: These teams perform the requested and assigned tasks. Kubernetes master controls them.
All containers in the pod share IP addresses, IPC, hostnames, and other resources. pod abstracts the network and storage of the underlying container. This makes it easier to move containers across the cluster.
Replication Controller- Controls how many copies of the same container run at a cluster location.
Service: This separates the working definition from the podcast. The Kubernetes service agent automatically gets the service request to the correct podcast, regardless of where it moves in the cluster, it has even been replaced.
Kubelet: This service runs on nodes, reads the manifest from the container and ensures that the defined container is active and running.
Kubectl: Command Line Configuration Tool for Kubernetes.
How does Kubernetes work?
The Kubernetes implementation is called a cluster. You can think of a Kubernetes cluster as two parts: a control plane (consisting of a master node or node) and a computer or work node).
The work node runs a panel consisting of containers. Each node is its own Linux environment, which can be a physical or virtual machine.
The master node is responsible for maintaining the desired state of the cluster, such as which applications are running and which container images they use. Actually, the job node runs applications and workloads.
Kubernetes runs on top of the operating system and interacts with containers running on the node.
The master Kubernetes node receives commands from the administrator (or the development operations team) and transmits those instructions to the server node.
This switch works with many services to automatically decide which node is best for the task. It then assigns resources and assigns dashboards on that node to perform the requested work.
The desired state of Kubernetes clusters defines which applications or other workloads should run, what images they use, what resources should be available to them, and other configuration details.
From the infrastructure point of view, the way containers are managed virtually unchanged. Your control over containers only happens at a higher level, giving you better control without micromanaging each individual container or node.
Some work is necessary, but it is mainly the problem of assigning Kubernetes hosts, defining nodes and defining pods.
This can be bare hardware servers, virtual machines, public cloud providers, private clouds, and hybrid cloud environments. One of the main advantages of Kubernetes is that it is suitable for many different types of infrastructure.
Can Kubernetes run without Docker?
Kubernetes can run without Docker and Docker can function without Kubernetes. But both perform better if used together. Docker can be installed on any computer to run containerized applications.
it can be used as container runtime for Cober’s orchestra. When Kubernetes program a container to a node, the kubelet on that node tells the dock to start the specified container.
Kubelet constantly collects the status of these containers from the dock and adds this information to the master. Docker pulls containers on the node and starts and stops them.
The difference between using Kubernetes and docker is that the automation system requires Docker to perform these actions, rather than having the administrator do them manually on all nodes in all containers.
Support a DevOps approach with Kubernetes
Developing modern applications requires a different process from the methods of the past. Devops can speed up the process from development to implementation of ideas.
DevOps is based on automating routine operational tasks and standardized environments throughout the application lifecycle. Containers support a unified development, delivery, and automation environment, and make it easy to move applications between development, test, and production environments.
Using Kubernetes to manage the lifecycle of containers and how to develop operations can help adjust software development and operations to support CI/CD pipes. With the right platform, you can make the best use of the cultural and process changes implemented, whether inside or outside the container.
Using Kubernetes in production
Kubernetes is open source and doesn’t offer any centralized support to get all your problems sorted out quickly. Therefore, it can be frustrating to implement Kubernetes while still running in a production environment.
For example, if you just install an engine in a car, it won’t work. It needs to be connected with a transmission, axles, and wheels. Just installing Kubernetes is not enough to have a fully functional platform. It needs additional features such as authentication, networking, security, monitoring, logs management, and other tools.