If you’ve spent much time around the tech world in the last seven years, chances are you’ve heard of Kubernetes. But what is Kubernetes and why is it so talked about?
Read on to learn all about Kubernetes, containerization, and the advantages these modern infrastructure methodologies bring.
What Is Kubernetes?
Kubernetes, often shortened to K8s or kubes, is an open-source containerization platform developed and released by Google. Originating from the Greek word for “pilot” or “helmsman,” Kubernetes is an all-in-one container management solution, which combines declarative configuration and automation to maximize efficient resource usage. Portable, flexible, and freely available, Kuberenetes represents one of the most significant advancements in IT since the development of the cloud.
Released for public usage in 2014, Kubernetes combines 15 years of Google’s experience scaling production workloads. A custom, in-house solution, Kubernetes remains at the core of Google’s expansive infrastructure, with the company generating over 2 billion containers weekly. As an open-source project available through the Cloud Native Computing Foundation (a joint project combining Linux, Google, Microsoft, and more), Kubernetes has become the go-to solution for organizations looking to scale across multi and hybrid cloud environments.
But to truly understand what helps set Kubernetes apart from other containerization software like Docker, you first have to understand what makes containers unique in the first place, and why Kubernetes’ ability to manage them at scale is so significant.
Advantages of Containerization
On the surface, containers share many similarities to virtual machines (VMs). Both are isolated instances with designated resources which allow administrators to compartmentalize larger systems into smaller, more efficient pieces. Unlike VMs though, containers have relaxed rules on their isolation, allowing applications within these containers to designate their resource needs but still share a singular operating system. This difference helps make containers more lightweight than virtual machines, easier to deploy and destroy as needed, and able to move across cloud instances and OS distributions more freely.
In addition, containers also lead to a higher degree of specialization, with most hosting only single applications or fragmented pieces of larger applications, known as microservices. This lets users divide up their machines to run multiple applications simultaneously, all utilizing the same kernel and hardware, but keeping workloads distinct. Not only does this save memory space and allow for maximum efficiency in resource utilization, but it can even minimize startup times as well.
Containers also provide an agile method for application development within cloud-native environments. Rather than building monolithic, singular applications, containers allow developers to build in pieces, easing the strains of developing, updating, and maintaining large applications. Because containers are decoupled from their underlying infrastructure, they can easily be moved across public cloud, private cloud, and bare metal environments with predictable performance and consistent functionality from development to deployment. This allows for a separation of development and operational concerns while maximizing the effective use of your system’s total available resources.
Features Inherent to Kubernetes
What sets Kubernetes apart from other containerization software is that beyond the ability to create and manage individual containers, Kubernetes establishes a dynamic system by which to group, manage, and automatically maintain large networks of containers. This orchestrative element helps set Kubernetes apart as a truly enterprise-grade containerization solution, able to easily scale on a massive level.
At its core, Kubernetes works by organizing and grouping systems of bare metal servers and virtual machines into larger webs of available resources. This process creates a supercomputer known as a cluster, a hybrid system with superior processing resources and network capabilities than any single machine. These clustered components are referred to individually as nodes, and are combined to more efficiently manage groupings of containers. Each node is capable of running pods, which in turn run the containers on your system.
Within each cluster, one node is designated as the master node, forming a layer of orchestration which supervises and delegates tasks to the other nodes in the cluster. This allows for automated scaling and failover protection by utilizing customizable deployment patterns. Additionally, the master node also monitors the health and stability of individual nodes and containers within the cluster, minimizing downtime by establishing an effective safety net for actively running containers. With automatic bin packing, simply designate the CPU and RAM allocations a container requires, and let Kubernetes fit your containers to your infrastructure automatically and efficiently.
It is important to note that while similar in some regards, Kubernetes is not a traditional Platform as a Service (PaaS) solution. Although it does offer building blocks which could be utilized to establish a development platform, Kubernetes’ operation at the container level, rather than the hardware level, keeps it distinct. Additionally, Kubernetes neither deploys source code to build your applications, nor does it provide built-in application-level services such as middleware, databases, or caches.
With a growing ecosystem of plugins and optional integrations, one of Kubernetes biggest advantages is its commitment to flexibility. With no limit to the types of applications and workloads supported, Kubernetes is designed to support a diverse selection of infrastructure solutions. Community-driven integrations keep Kubernetes current, and widespread acceptance means many providers offer brand-specific tie-ins for easier integration of their products into existing clusters.
The following is a list of important terms associated with Kubernetes:
- Cluster – a cluster is a collection of nodes running containerized applications being managed by Kubernetes. Each cluster is essentially a supercomputer, pulling the combined available resources of the hardware and VM nodes it’s composed of and moving containers freely throughout.
- Pod – a pod is the smallest organizational unit in the Kubernetes object model. Pods exist within nodes and are used to host individual or grouped containers inside the cluster.
- Control Plane – also known as the master node, the control plane is the orchestration layer within the cluster which designates and supports the other nodes in their tasks, providing interfaces to define, deploy, and manage containers. Larger clusters, known as “high availability clusters,” may utilize multiple master nodes in unison.
- Worker Node – all the nodes in the cluster other than the master node (or nodes if there are multiple), are considered “worker” or “compute” nodes. These are the nodes which actually run the pods/containers/applications within the cluster, receiving their instructions from the master node.
- Container Runtime – the container runtime is the software which sits on top of the machine’s operating system, coordinating resource usage between the containers and the hardware they share. The container runtime’s role in containerization is similar to the role of a hypervisor in the creation of virtual machines.
- Kubelet – the kubelet is a service which runs on each worker node, ensuring the containers within the associated pods are running according to the container manifest.
- Kubectl – kubectl is a command line interface tool for configuring Kubernetes.
- Kubeproxy – kubeproxy is a service which allows for communication between worker nodes by maintaining the system’s network rules for each node.
And there you have it! For more information on Kubernetes and its role within complex, hybrid cloud environments, check out our blog post, Hybrid Cloud Kubernetes Clusters.
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