Kubernetes is defined as an open-source platform that is used for container orchestration. This scalable and portable solution automates several processes during containerized applications’ deployment, scaling, and management. This article covers the working, architecture, and importance of Kubernetes.
Table of Contents
What Is Kubernetes?
Kubernetes is an open-source platform that is used for container orchestration. This scalable and portable solution automates several processes during containerized applications’ deployment, scaling, and management.
Kubernetes Cluster Architecture
Originally designed and developed by Google, Kubernetes has helped shape the tech giant’s reliance on containers, particularly for its cloud services. The Kubernetes platform is the successor of Borg, a cluster management system used internally by Google engineers. The Kubernetes project was open-sourced by Google in 2014 when it was transferred to the Cloud Native Computing Foundation–a sub-foundation of the Linux Foundation, a non-profit organization–as a seed technology.
Also known as K8s (for the eight letters between ‘K’ and ‘s’), Kubernetes is originally a Greek term meaning pilot or helmsman. This solution’s primary aim is to simplify container orchestration automation, boost reliability, and scale down the resource requirements of day-to-day operations. The platform is supported by a vast and rapidly expanding ecosystem, with tools, services, and support widely available for users.
Containers and Kubernetes
The demand for containerized applications has seen an explosive increase in the last decade. A March 2022 projection by Gartner pegs container adoption by global organizations at 90 percent by 2026.
A container is a comprehensive software package containing all the components required for independent operation. This includes system tools, preset configurations, libraries, and an executable program.
Containers can be viewed as lightweight, specialized adaptations of virtual machines with less stringent isolation properties. Just like a virtual machine, a container also has access to the CPU’s processing power and its own filesystem, process space, and memory. Containers are decoupled from the fundamental infrastructure of the platform, making them portable across operating systems and cloud platforms.
More and more software-first enterprises are leveraging containers to create bundles and design and execute their applications more effectively. However, as the container architecture of an organization scales up, measures need to be taken to minimize container downtime and mitigate its effects.
Kubernetes addresses this by providing users with a robust framework for running distributed container systems. Engineers rely on the platform for automated scaling and failover, provisioning of deployment patterns, and more.
| What Is Kubernetes Used For?
Kubernetes is an automated orchestration tool for containers. It allows for the seamless execution of operational tasks related to container management. This platform has built-in commands for application deployment, update rollouts, scaling up or down, application monitoring, and many more functions. Simply put, users only need to tell Kubernetes where the application needs to be executed, and it will handle almost everything else. |
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How Does Kubernetes Work?
Kubernetes is vendor agnostic and compatible with most leading server and cloud solutions, including Azure Container Service, Amazon EC2, and IBM Software. It also works with bare-metal configurations using CoreOS and similar solutions, as well as vSphere, Docker, libvirt and Linux kernel-based virtual machines.
But what exactly does Kubernetes do? Well, massive container-powered enterprises typically need multiple Linux container instances to sustain all their application needs. This becomes especially necessary as applications increase in complexity, for instance, by adopting microservices for their communication needs.
Managing individual containers becomes an uphill task as an organization’s container infrastructure scales up. Developers must schedule container deployment for particular machines, manage networking, scale-up resource allocation according to workload, and more.
That’s where Kubernetes comes in! This container orchestration system allows engineers to manage the containerized application lifecycle throughout the fleet. This ‘meta-process’ allows users to simultaneously automate scaling and deployment for numerous containers.
Kubernetes gives containers visibility using either DNS or IP addresses. Additionally, Kubernetes groups together the containers that run the same application. The containers replicate each other’s functionality and balance the load of incoming requests among themselves. The load in high-traffic containers is balanced, and network traffic is distributed to ensure a stable deployment.
Container groups are managed by Kubernetes, which works to ensure seamless operations. This automated process serves as an administrator that supervises the operations of containerized application groups. Orchestrators such as Kubernetes take care of numerous processes, such as restarting a container or scaling up its throughput.
Kubernetes operates as a cluster in several nodes, making applications more robust. This framework also supports automated static and dynamic scaling. Automatic resizing of the number of replications based on memory and CPU utilization is also supported. Once a specific threshold percentage is crossed, Kubernetes creates a new pod to ensure optimized load balancing.
Storage orchestration is another function of Kubernetes. This enables users to automate the mounting of their preferred storage system, including local and public clouds.
With Kubernetes, users can define the preferred state for deployed containers. The framework then takes a controlled approach to modifying the actual state to the desired state. Simply put, Kubernetes can automate rollouts and rollbacks. For instance, it can be automated to form new containers, remove existing ones, and adopt resources to a newly created container.
Kubernetes is also used to manage secrets and configurations by allowing for the storage and management of sensitive data. This includes passwords, SSH keys, and OAuth tokens. With Kubernetes, it is possible to deploy and update application configurations and secrets without the need to rebuild container images. This arrangement also prevents secrets from being exposed in the stack configuration.
Finally, automatic bin packing and self-healing are two other salient features of Kubernetes.
In the case of the former, the user needs to provide a cluster of nodes that the platform can leverage for running containerized tasks. Once the CPU and memory specifications of each container are added to Kubernetes, it crafts the containers onto the provided nodes to ensure optimized resource consumption.
In the latter, the framework can restart failed containers, terminate containers that fail to respond favorably to a user-defined health check, replace containers as required, and keep containers hidden from clients before they are ready.
Tip: minikube is a rudimentary platform for those looking to explore Kubernetes. This tool allows users to run Kubernetes on a virtual machine on their computer. It operates as a local cluster and is scalable to any size. With minikube, users can try out Kubernetes without engaging in cloud deployments or infrastructure management.
| How To Stop All Kubernetes Pods?
Kubernetes does not offer users a way to stop or pause (and later resume) the present state of a pod. To delete a pod, run this command: kubectl delete pod [POD_NAME] Once the pod is deleted successfully, the terminal will respond with pod [POD_NAME] deleted |
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Understanding the Kubernetes Architecture
Now that we have an outline of how Kubernetes works let’s take a look at the specific architectural components that make this container orchestration framework tick.
1. Pod
Pods are simply groups of containers–the smallest architectural unit managed by Kubernetes. Each pod has one IP address shared by all its containers. Resources such as storage and RAM are shared by all the containers in the same pod, allowing them to operate as one application.
A pod can contain a single container when the application that needs to be executed is a single process. On the other hand, multi-container pods make deployment configuration easier when compared to manually setting up shared resources among containers. Such pods are useful for more complex configurations; wherein numerous processes work together while sharing the same data volumes.
Pods primarily operate using ephemeral storage, meaning they lose all data when replaced or destroyed. Cloud platforms managed by Kubernetes do not require the creation of disk volume for pods. Users must only claim it through a particular volume configuration, and the volume will be provisioned once the pod is created.
2. Deployment
Deployments allow users to specify the scale at which the application needs to operate. Users must define their preferences for pod replication on the Kubernetes nodes.
Deployments outline the preferred quantity of identical pod replications to be executed. Additionally, they prescribe the favored strategy for deployment updates.
Pods are added or removed to create the desired state for the application, while pod health is tracked to ensure optimum deployments.
3. Service
The lifetime of a pod is volatile, with every aspect of its existence being subject to change. Kubernetes is known to treat pods as expendable, transitory instances; a pod being destroyed is a commonplace occurrence. In such a scenario, Kubernetes simply replaces the pod to avoid application downtime.
A Kubernetes service is an abstraction over the pods. This component is the interface that application users primarily engage with. Even though replaced pods might be assigned new names and IP addresses internally, services ensure that these details remain the same to the network at large.
4. Node
Nodes are the physical or virtualized machines that execute the assigned task. They are responsible for running and managing pods. Nodes create collections of pods that operate together, like pods group containers with similar operating parameters. When the container infrastructure operates on a large scale, users can assign tasks to nodes, which are then delegated to pods with the available bandwidth.
5. Control plane
Administrators and users access Kubernetes through the control plane, which allows them to manage nodes effectively. This component is responsible for controlling the interactions between Kubernetes and applications. Operations are assigned to the control plane either by linking to the machine and executing command-line scripts or via HTTP calls.
6. Cluster
Simply put, a cluster is an aggregation of all the above components. Clusters contain Kubernetes software nodes and access the same memory and computing resources.
Horizontally scaling up the cluster by adding more nodes to this ‘node pool’ leads to all the pods being redistributed in a configuration that includes the new nodes. Cloud infrastructures such as Google Cloud and AWS automate the management of clusters. Users only need to provide the physical specs and the number of nodes.
Components of the control plane and nodes
This sub-section lists the three components in each, the control plane and individual worker nodes.
1. Control plane
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- API server: This element exposes a REST interface to the cluster. All operations against services, pods and other components are programmatically executed through endpoint communications powered by the API server.
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- Controller manager: This element ensures seamless operations of the cluster’s shared state. The controller manager’s responsibility is to supervise controllers that respond to specific events, such as the deactivation of a node.
Thanks to this element, the cluster can continuously maintain the specific state of the application. It serves as a control loop that oversees the shared state through the API server and executes modifications in an attempt to migrate the current state toward the preferred state. The controller manager also monitors cluster health and bandwidth for workloads.
For instance, an unhealthy node may not allow users to access its pods. That’s when the controller manager steps in to schedule new pods with the same configuration in another node, thus ensuring that the expected state of the cluster is maintained constantly.
The controller manager contains built-in controllers that offer primitives. These primitives are associated with specific workload classes, including stateful, stateless, run-to-completion jobs, and scheduled cron jobs. Operators and developers can leverage these primitives when packaging and deploying applications. - Scheduler: This element assigns tasks at the node level based on resource availability. Additionally, it monitors resource capacity to ensure that worker node performance levels meet the requisite parameters. Operations personnel can declaratively prescribe the resource model, after which the scheduler provisions and allocates the appropriate resources to all workloads accordingly.
- Controller manager: This element ensures seamless operations of the cluster’s shared state. The controller manager’s responsibility is to supervise controllers that respond to specific events, such as the deactivation of a node.
2. Worker node
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- Kubelet: A key function of the Kubelet is enforcing the instructions transmitted by the head node cluster to the pods. This ‘tiny program’ runs on the worker node and negotiates between it and the control plane.
Additionally, it is responsible for tracking the state of a pod and ensuring seamless responsiveness of all containers. It does so by transmitting a heartbeat signal to the control plane every few seconds. A node is classified as ‘unhealthy’ if a replication controller fails to receive this signal.
- Kubelet: A key function of the Kubelet is enforcing the instructions transmitted by the head node cluster to the pods. This ‘tiny program’ runs on the worker node and negotiates between it and the control plane.
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- Kube proxy: This element routes traffic being transmitted from the service into a node. It is responsible for accurately forwarding work requests to the appropriate containers. Additionally, the Kube proxy enforces network rules and regulates incoming and outgoing traffic at the node level. The ingress is similar to the Kube proxy; however, it operates at the cluster level.
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- etcd: This element is a lightweight and persistent distributed key-value store. It is leveraged by Kubernetes to transmit data about the overall condition of specific clusters. Apart from this, nodes can reference the global configuration information stored by the etcd to undergo automated and independent configuration upon being regenerated. Users can access the etcd database solely through the API server.
| How To Stop All Kubernetes Deployments?
One way to stop a deployment is by deleting it. To do so, use this command: kubectl delete deployment [DEPLOYMENT_NAME] Alternatively, you can delete deployments in bulk through the cloud console:
Tip: To see the list of running deployments, use this command in Master node: kubectl get deploy |
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Importance and Benefits of Kubernetes
This open-source container orchestration solution is increasingly being adopted by enterprises looking to enhance their application administration capabilities in heterogeneous technological environments.
The five key benefits of Kubernetes:
Importance and Benefits of Kubernetes
1. Improves development efficiency
Kubernetes simplifies development, thus making deployment and release processes more efficient. For instance, this framework allows engineers to undertake container integration and enables administrators to access storage resources from various vendors seamlessly.
Additionally, microservices-centric architectures can rely on Kubernetes to create a decentralized development ecosystem. In such an arrangement, one can compartmentalize the elements of the application into numerous functional units linked to each other using APIs. Development teams can also be separated into small, specialized sub-groups specializing in one feature each. This can greatly improve development efficiency.
2. Minimizes cost inefficiencies
Kubernetes automates the modulation of resource allocation processes according to the actual needs of applications.
Intelligent container management through Kubernetes enables enterprises to minimize ecosystem management costs and boost scalability across operational environments. Additionally, the need for rudimentary manual operations is minimized at the infrastructure level through cloud platform integrations and dynamically native autoscaling (HPA, VPA) logic.
The automation capabilities provided by Kubernetes also give IT teams freedom from several system management tasks, granting them the resources they need to focus on value addition. Finally, platform-agnostic operations allow organizations to decide which resources they prefer–public cloud, private cloud, or on-premise–for specific workloads.
3. Enhances availability & scalability
Organizations can scale up the resource allocation for specific components of their applications by using Kubernetes. This allows for flexible, need-based scalability and facilitates dynamic peak management. For instance, Kubernetes can scale up the throughput of an ecommerce application for the hours during which a large sale has been organized.
Native autoscaling APIs such as HPA and VPA allow Kubernetes to place dynamic requests for resource allocation and even scale the infrastructure back down once the need is fulfilled. This helps ensure the impeccable availability of the application even during peak demand.
4. Supports multi-cloud environments
Containerization backed by Kubernetes allows users to leverage multi-cloud and hybrid cloud environments to their total capacity. With Kubernetes, applications can operate in all leading public and private cloud environments without suffering from any loss of function or other effects on performance.Â
This feature also has a secondary benefit: minimizing vendor lock-in risk. Kubernetes helps maximize the interoperability of supported technological solutions and prevents enterprises from relying on a single supplier.
5. Simplifies cloud migration
As more organizations adopt a cloud-first approach, Kubernetes is a helpful solution for simplifying and accelerating the migration process.
Shifting on-premise applications onto a cloud platform can be achieved through numerous methodologies, including lift and shift (simply uploading the application without coding changes), replatforming (making the minimum modifications required to enable functioning in the new environment), and refactoring (rewriting the application entirely for the new platform).
While refactoring is the most resource-intensive alternative, completing it on an on-premise system using containerized architectures combined with Kubernetes is the most effective and long-term approach to cloud migration.
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Takeaway
Engineers are increasingly adopting Kubernetes to make the hassle-free iteration and release process for applications possible through code-based provisioning of dependencies. This container orchestration solution is one of the most preferred tools for delivering and managing containerized, legacy, and cloud-powered applications, as well as for apps undergoing refactoring for migration to a microservices environment.
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