What is Kubernetes?
It is an open-source container orchestration tool that allows cloud applications to run on an elastic web server architecture. We may use Kubernetes to outsource data centres to public cloud service providers or for large-scale web hosting. Website and mobile applications with complicated custom code can be deployed on commodity hardware using Kubernetes to save money on web server provisioning with public cloud hosts and to speed up software development.
The Cloud Native Computing Foundation, which promotes the implementation of open networking standards in cloud data centre management software, includes Kubernetes (often abbreviated to "K8s"). Kubernetes uses the most common container virtualization standard, Docker. For programming teams, Docker provides integrated software lifecycle development tools. RancherOS, CoreOS, and Alpine Linux are some of the most common operating systems for container use. Container virtualization differs from hypervisor-based VM and VPS tools in that it typically needs a smaller operating system footprint in development.
Features of Kubernetes
Kubernetes has the ability to automatically provision web servers based on the amount of web traffic in progress. Web server hardware can be found in a variety of data centres, on a variety of hardware platforms, and across a variety of hosting providers. Kubernetes scales up web servers in response to software application requests, then downscales web server instances during downtimes. For web traffic routing to web servers in operations, Kubernetes also has advanced load balancing capabilities.
EXPLAINING HOW KUBERNETES WORKS?
An infrastructure robust enough to handle clustering demands and the stress of dynamic orchestration is needed for a modern application packaged as a collection of containers and deployed as microservices. An infrastructure like this should provide primitives for scheduling, tracking, updating, and moving containers between hosts. The underlying compute, storage, and network primitives must be treated as a pool of resources. Each containerized workload should be able to use the resources available to it, such as CPU cores, storage units, and networks.
Kubernetes is an open-source distributed framework for running containerized applications at scale by abstracting the underlying physical infrastructure. Kubernetes manages an application during its entire life cycle, and it is made up of containers that have been grouped together and coordinated into a single entity. As seen in the diagram below, an efficient cluster manager layer allows Kubernetes to decouple this framework from its supporting infrastructure effectively. DevOps teams will concentrate on managing deployed workloads instead of dealing with the underlying resource pool, which is handled by Kubernetes, once the Kubernetes infrastructure is completely configured.
Kubernetes is a container-based operating system.
Kubernetes is an example of a distributed system that has been well-architected. It considers all of the devices in a cluster to be part of a single resource pool. It performs the functions of a distributed operating system by efficiently scheduling, allocating resources, tracking infrastructure health, and even preserving the desired state of infrastructure and workloads. Kubernetes is a container-based operating system that allows modern applications to operate across several clusters and infrastructures in the cloud and private data centre environments.
Kubernetes, like every other mature distributed framework, has two layers: head nodes and worker nodes. The control plane, which is responsible for scheduling and controlling the life cycle of workloads, is usually run by the head nodes. The workhorses that run applications are the worker nodes. A cluster is formed by a series of head and worker nodes.
The command-line interface (CLI) or third-party tools are used by the DevOps teams managing the cluster to communicate with the control plane's API. The users access the programs running on the worker nodes. The applications are made up of one or more container images that are maintained in an image registry that is open to the public.
The Kubernetes Control Plane
The components of Kubernetes that provide the core functionalities are managed by the control plane:
- Exposing the Kubernetes API
- Scheduling workload deployments
- Controlling the cluster
- Guiding communications across the entire system
The head tracks the containers running in each node and all the registered nodes' health. Container images, which serve as deployable objects, must be accessible via a private or public image registry to the Kubernetes cluster. The container runtime allows the nodes in charge of scheduling and running the applications to access the registry's images.
The control plane is run by the Kubernetes head node, which includes the following components:
It works by acting as the single source of truth by representing the cluster's overall state at any given time. To keep an application in the desired state, various other components and services monitor changes to the etcd store. That state is specified by a declarative policy, which is essentially a document that specifies the ideal environment for that application so that the orchestrator can work toward it. This policy specifies how the orchestrator deals with an application's different assets, such as the number of instances, storage requirements, and resource allocation.
The API server only accesses the etcd database. The API server is used by any part of the cluster that needs to read or write to, etcd.
API Service Provider
The API server exposes the Kubernetes API via JSON over HTTP, providing the orchestrator's internal and external endpoints with a representational state transfer (REST) interface. A request to the API server may be made using the CLI, the web user interface (UI), or another tool. The server processes and validates the request before updating the API objects' state in etcd. Clients can configure workloads and containers through worker nodes as a result of this.
The scheduler determines which node each workload should run on based on its resource availability evaluation and then monitors resource usage to ensure the pod does not surpass its allocation. It keeps track of resource requirements, availability, and several other user-supplied constraints and policy guidelines, such as quality of service (QoS), affinity/anti-affinity requirements, and data locality. The resource model can be described declaratively by an operations team. The scheduler interprets these statements as guidelines for provisioning and allocating the appropriate resources to each workload.
The controller-manager, which is part of the brain, is the part of Kubernetes' architecture that gives it its flexibility. The controller manager's job is to make sure that the cluster stays in the desired application state all of the time, thanks to a well-defined controller. A controller is a control loop that monitors the cluster's shared state through the apiserver and makes adjustments to try to bring it closer to the desired state.
The controller keeps nodes and pods in a stable state by continuously tracking the cluster's health and its workloads. When a node becomes unhealthy, for example, the pods that run on it will become unavailable. The controller's role, in this case, is to schedule the same number of new pods in a different node. This operation ensures that the cluster is still in the planned state.
The controller-manager in Kubernetes comes with a collection of built-in controllers. These controllers include primitives tailored to specific workload types, such as stateless, stateful, scheduled cron jobs and run-to-completion jobs. These primitives can be used by developers and operators when packaging and deploying applications in Kubernetes.
The following posts in this series delve deeper into Kubernetes architecture, including the core components of worker nodes and workloads, services and service discovery, networking and storage, and networking and storage.
Advantages of Kubernetes
The key benefit of Kubernetes is the ability to run an automated, elastic web server infrastructure in production without having to rely on Amazon's EC2 service. Most public cloud hosting services support Kubernetes, and all of the major providers have competitive pricing. Kubernetes allows a company's data centre to be fully outsourced. Kubernetes can also be used in development to scale web and mobile applications to the highest levels of traffic. Kubernetes enables any organization to run its software code at the same degree of scalability as the world's largest businesses while paying less for hardware resources in a data centre.
Why is Kubernetes so widely used?
The container management framework built by Google has quickly become one of the most successful open-source projects ever.
In recent years, Kubernetes, an open-source container management framework, has grown in popularity. It is now one of the greatest success stories in open source, being used by the largest companies in a wide variety of industries for mission-critical tasks.
We saw massive, monolithic apps slowly turn into multiple, agile microservices as the computing environment became more distributed, network-based, and cloud-based. These microservices allowed users to scale key application functions individually and manage millions of customers. On top of this paradigm shift, we've seen enterprise-level technologies like Docker containers evolve, providing a consistent, compact, and simple way for users to create microservices quickly.
As Docker grew in popularity, managing microservices and containers became a top priority. That's when Google, which had been operating container-based infrastructure for years, took the risky step of releasing Borg, an internal project. Google's services, such as Google Search and Gmail, relied heavily on the Borg system. Because Google decided to open-source its infrastructure, every organization worldwide can now operate its infrastructure like one of the world's top companies.
Largest open-source groups in the world.
Kubernetes competed with other container-management frameworks after its open-source releases, such as Docker Swarm and Apache Mesos. One of the reasons Kubernetes has recently surpassed these other systems is the system's community and support: It's one of the biggest open-source groups (over 27,000 stars on GitHub), with contributions from thousands of organizations (1,409 contributors), and is located within the Cloud Native Computing Foundation, a massive, neutral, open-source foundation (CNCF).
Some of the largest business firms, including Microsoft, Google, and Amazon Web Services, are members of the CNCF, which is part of the broader Linux Foundation. Also, the CNCF's business membership continues to expand, with SAP and Oracle joining as Platinum members only a few months ago. These companies' participation in the CNCF, where the Kubernetes project is prominent, demonstrates how much they trust the group to deliver a portion of their cloud strategy.
Kubernetes' enterprise community has grown as well, with vendors offering enterprise versions with enhanced security, manageability, and support. Red Hat, CoreOS, and Platform 9 are among the few companies that have made Enterprise Kubernetes a vital part of their long-term strategy and have invested extensively in keeping the open-source project alive.
Taking advantage of the hybrid cloud's strengths
Another explanation why businesses are implementing Kubernetes at such a rapid rate is that it can run on any cloud. The need for hybrid cloud technology is important because most companies share assets between their current on-premises data centers and the public cloud.
Kubernetes can be installed in a company's on-premises data center, in one of the many public cloud environments, or even as a service. Kubernetes abstracts the underlying infrastructure layer, allowing developers to concentrate on developing applications and then deploying them to each environment. This boosts a company's Kubernetes adoption by allowing it to run Kubernetes on-premises while still pursuing its cloud strategy.
Usage cases from the real world
Another explanation for Kubernetes' continued growth is that big companies use it to address some of the industry's most pressing issues. Some of the companies that have reported Kubernetes use cases include Capital One, Pearson Education, and Ancestry.com.
One of the most well-known use cases demonstrating the strength of Kubernetes is Pokemon Go. The online multiplayer game was thought to be fairly successful before its release. However, it took off like a rocket as soon as it was launched, generating 50 times the predicted traffic. Pokemon Go could scale massively to keep up with the unpredictable demand by using Kubernetes as an infrastructure overlay on top of Google Cloud.
What began as a Google open source project, Kubernetes is now open-source software that is part of a large foundation (CNCF) with several enterprise members. It is backed by 15 years of experience running Google services and a legacy from Google Borg. With mission-critical apps in finance, it's becoming increasingly popular, massively multiplayer online games like Pokemon Go, educational institutions, and traditional business IT all using it. When taken as a whole, all signs point to Kubernetes continuing to gain traction and staying one of the open source's biggest success stories.
Combining Docker and Kubernetes:
Docker containers will assist you in segregating and packing your applications, while Kubernetes will handle deployment. On the other side, Kubernetes orchestrates the containers. Kubernetes, like Docker Swarm, is a container orchestration framework for Docker containers with more broadly available consequences. Similarly, it is well-known for methodically scaling clusters of nodes.
In the Kubernetes environment, pods are used as scheduling units. To achieve high availability, the pods are dispersed nodes. When using a Kubernetes cluster, we can easily run a Docker install. By integrating with the Docker engine, Kubernetes helps to manage the scheduling and execution of Docker containers on kubelets. The Docker engine is in charge of running and managing the actual container image generated by running the 'Docker construct.'
Kubernetes and Docker are not interchangeable because they seem to be based on separate technologies. When they are used together, however, they can yield the best results. Docker and Kubernetes also make container management and deployment easier in a distributed architecture.
Kubernetes formalizes key concepts like service discovery, load balancing, and network policies. You will start running and managing your applications at a wide scale once you understand the combined benefits of Docker and Kubernetes.
We've seen an increase in demand for cloud computing, containerization, and orchestration technologies as businesses move their infrastructure and architecture to meet the current technology trend of a cloud-native and data-driven age. Names like Docker and Kubernetes, which have revolutionized how we create, build, deploy, and ship applications at scale, are hard to overlook when discussing cloud-native.
Docker makes it easier to "create" containers, while Kubernetes makes it possible to "manage" them in real-time. To package and ship the software, use Docker. To deploy and scale your software, use Kubernetes. Startups and small businesses with fewer containers can normally handle them without Kubernetes, but as businesses expand, their infrastructure needs will increase, and the number of containers will grow as well, making management more difficult. This is where Kubernetes enters the image.
Docker and Kubernetes, when used together, are digital transformation enablers and tools for modern cloud infrastructure. For quicker device deployments and releases, using both has become the new standard in the industry. Understanding the high-level differences between Docker and Kubernetes when constructing your stack is strongly recommended.
Regardless of the cloud journey, you select, let containers assist you in unraveling the mysteries of cloud computing.
- The code of the developers is moved to Git.
- Jenkins for C is used to construct and evaluate the code.
- We'll write Ansible playbooks to deploy on AWS using Ansible as a deployment tool.
- After the construct process from Jenkins, we'll add JFrog Artifactory as the repository manager. The objects will be stored in Artifactory.
- Ansible can connect to Artifactory, download the objects, and deploy them to an Amazon EC2 case.
- The SonarQube will assist in code review and provide static code analysis.
- Then, as a containerization method, Docker is introduced. We'll deploy the app to a Docker container in the same way we did on Amazon EC2 by creating a Docker file and Docker photos.
- We'll use Kubernetes to build a Kubernetes cluster, and we'll be able to deploy using Docker images once the above setup is complete.
- Finally, we'll control the infrastructure with Nagios.
Microservices enable businesses to break down large monolithic applications into smaller components that can be packaged and deployed independently. Microservices increase the agility, scalability, and durability of apps by allowing them to be upgraded, modified, and redeployed more quickly.
Docker and Kubernetes are examples of tools that work together to help businesses deploy and scale applications as required.
Kubernetes has taken off in the cloud market like wildfire, with adoption growing year after year. Containers as a service (CaaS) or platform as a service (PaaS) models are used by IBM, Amazon, Microsoft, Google, and Red Hat to provide managed Kubernetes. Kubernetes is now being used in development at a large scale by several multinational corporations.
Docker is a brilliant piece of software. According to the "RightScale 2019 State of the Cloud Report," Docker is winning the container market with a massive year-over-year adoption increase.
Docker is used by millions of developers, who download 100 million container images every day, and Docker Enterprise Edition is used by over 450 companies, including some of the world's largest corporations. Docker and Kubernetes will continue to exist for many years to come.