"Kubernetes is easy," said no one ever.
I'll gladly admit how intimidating Kubernetes can look on the outside. For starters, an overwhelming amount of content exists covering the already complex topic.
On top of that, it is challenging to figure out what terminology and concepts you need to understand when getting started with Kubernetes.
In the world of Kubernetes, there are many terms that you'll likely be unfamiliar with at times.
Luckily, we've got you covered with our quick and dirty guide to Kubernetes terminology.
What is Kubernetes?
Kubernetes is a popular open-source platform for automating the deployment, scaling, and management of containerized applications. Developed by Google in 2014, it's now maintained by the Cloud Native Computing Foundation (CNCF), and is used by companies around the world.
Kubernetes terminology you need to know
Here is a list of the most common Kubernetes terms you should familiarize yourself with when getting started.
Cluster: A set of worker machines, called nodes, that run containerized applications orchestrated by a control plane, also called the kubernetes master.
Container: A lightweight and portable executable image that contains software and all of its dependencies.
Controller: Control loops that watch the state of your cluster and then make or request changes when needed.
Custom Resource: An extension of the kubernetes API defined by an external developer. Defines an api spec that the kubernetes API will support all the basic REST operations for, while a custom controller will listen to changes to the resource to perform reconciliations of the clusters state in response.
Deployment: A kubernetes resource that defines how many replicas should be running at any given time, how they should be updated, etc., and gives them labels so they can be referenced easily.
Node: A physical or virtual machine that runs containers as part of a Kubernetes cluster. A node is a server running the Kubernetes software. The nodes are managed by the master node and are responsible for scheduling containers across the cluster and storing data on disk.
Kubeadm: A tool that helps you set up a secure Kubernetes cluster quickly and easily, especially on-premises.
Kubelet: A daemon that runs on each node and takes instructions from the kubernetes api to perform any operations on that node in response, such as spawning new containers, provisioning ips, etc.
Namespace: Allow you to organize your cluster and set up logical divisions between domains or functions. Once set up, you can define policies and access rules for each. They simplify container management and reduce the risk of large-scale failure.
Pod: A group of one or more containers that are treated as a single entity by Kubernetes. Pods share an IP address and have their own filesystem namespace (similar to a chroot jail). Pods are created by using the pod kubernetes resource, which has a list of container specifications.
StatefulSet: Manages the deployment and scaling of a set of Pods, and provides guarantees about the ordering and uniqueness of these Pods alongside automating the creation and management of a persistent volume for each pod.
Why use Kubernetes in 2023?
Kubernetes is used by companies like Google and Amazon, and it's built to be highly scalable, so it can handle thousands of containers at once. It's also compatible with all major cloud platforms like AWS, GCP, and Azure.
Kubernetes allows you to run your application on multiple cloud providers or a combination of on-premises and cloud, allowing you to avoid vendor lock-in. In addition, it has a vibrant open-source community full of automation to do things like simplifying provisioning load balancers, managing secure networking with service meshes, automating DNS management, and much more.
Every engineering leader that I have spoken with agreed that Kubernetes is an extremely powerful tool, and developers at companies of all sizes can immediately reap the benefits of using it for their projects.
How does Kubernetes work?
Kubernetes allows you to define your application's components in separate containers that can be deployed onto any node in your cluster.
The master then schedules workloads across the cluster based on resource requirements like CPU or memory usage. This means you don't need to worry about scaling up or down; Kubernetes will automatically scale up when needed, and scale down when not needed anymore.
When you use Kubernetes, you can also easily add new features or upgrade existing ones without being concerned about the underlying infrastructure. You can also manage resources like CPU and memory dynamically without worrying about running out of resources.
It has a lot of features that make it a great option for running containerized applications, including
- Multiple apps on one cluster
- Automatically scaling up or down based on demand
- High availability and reliability
Kubernetes provides several key benefits to users:
- It simplifies application deployment, scaling, and management.
- It helps users avoid vendor lock-in by allowing them to run multiple instances of the same application on different platforms (e.g., Amazon Web Services).
- It allows users to easily scale applications up or down as needed, which allows them to take advantage of unused capacity while avoiding overspending on resources they don't need at any given time.
- Has built-in self-healing for all of your running containers and ships with readiness and liveness checks. When containers go down or are in a bad state, things often return to the status quo automatically or with plug-and-play debugging workflows.
There are a number of alternatives to Kubernetes. The most commonly used alternatives include Docker Swarm, Amazon ECS (Elastic Container Service), Apache Mesos, and Rancher.
One of the more common questions we get asked is whether or not it makes sense to invest time and resources into Kubernetes. We ultimately believe that Kubernetes is worth the investment (in terms of engineering resources) for most organizations.
If you have the right engineers, enough time, and resources to effectively run and upkeep Kubernetes, then your organization is likely at a point where Kubernetes makes sense.
I understand that these are not trivial prerequisites, but if you can afford to hire a larger engineering team you are likely at a point where your users heavily depend on your product to be operating at peak performance constantly.
However, if you’re considering deploying open-source applications onto Kubernetes, it has never been easier to do so than with Plural.
It requires minimal understanding of Kubernetes to deploy and manage your resources, which is unique for the ecosystem.
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